Peroxisome proliferator-activated receptors (PPARs) are ligand-activated nuclear receptors which regulate lipid and glucose metabolism as well as inflammation. In this presentation, we will review recent findings on the pathophysiological role of PPARs in the different stages of non-alcoholic fatty liver disease (NAFLD), from steatosis development to steatohepatitis and fibrosis, as well as the preclinical and clinical evidences for potential therapeutical use of PPAR agonists in the treatment of NAFLD. PPARs play a role in modulating hepatic triglyceride accumulation, a hallmark of the development of NAFLD. Moreover, PPARs may also influence the evolution of reversible steatosis towards irreversible, more advanced lesions. Large controlled trials of long duration to assess the long-term clinical benefits of PPAR agonists in humans are ongoing.

Non-Alcoholic Steatohepatisis and CVD – Meta inflammatory disease

NAFL — abnormal Lipid accumulation

NASH >> Balooning, FIbrosis inflamation

Resolution of NASH is associated with reduction of Fibrosis (Golden – 505 trial)

FGF21 is a hormone with anti-obesity and hepatoprotective properties. However, the beneficial effects of FGF21 are limited by a relatively short half-life in circulation. We discovered that fibroblast activation protein (FAP), an endopeptidase overexpressed in liver with cirrhosis, cleaves and inactivates FGF21. Pharmacological inhibition of FAP increases endogenous levels of active FGF21, thus making FAP a promising target for the treatment of non-alcoholic-steatohepatitis (NASH).

NASH patients typically have metabolic syndrome including diabetes, dyslipidemia, obesity, and primarily die of cardiovascular disease. Hypothyroidism at the level of the thyroid gland and liver-specific hypothyroidism are common in NASH. Based on clinical and preclinical data, Thyroid receptor beta agonists decrease insulin resistance, reduce LDL-C, triglycerides fatty liver, inflammation and fibrosis in NASH. The target will also provide CV benefit to patients with NASH. MGL-3196 is a highly THR-ß selective liver-directed once daily oral medication that has shown excellent safety and lipid-lowering efficacy in humans; unlike prior thyroid receptor agonist(s), no cartilage findings in chronic toxicology or ALT increases in human studies. MGL-3196 is being advanced in Phase II studies in patients with genetic dyslipidemia or NASH.

Madrigal Portfolio of drugs:

MGL-3196: First-in-Class THR-Beta Agonist – discovered first at ROCHE – THR-beta selective targeted to the Liver – regulated by THR-Alpha – in Phase II – no side effects on bone

Scientists from Duke-NUS Medical School (Duke-NUS) have derived a structural model of a transporter at the blood-brain barrier called Mfsd2a. This is the first molecular model of this critical transporter, and could prove important for the development of therapeutic agents that need to be delivered to the brain — across the blood-brain barrier. In future, this could help treat neurological disorders such as glioblastoma.

Currently, there are limitations to drug delivery to the brain as it is tightly protected by the blood-brain barrier. The blood-brain barrier is a protective barrier that separates the circulating blood from the central nervous system which can prevent the entry of certain toxins and drugs to the brain. This restricts the treatment of many brain diseases. However, as a transporter at the blood-brain barrier, Mfsd2a is a potential conduit for drug delivery directly to the brain, thus bypassing the barrier.

In this study, recently published in the Journal of Biological Chemistry, first author Duke-NUS MD/PhD student Debra Quek and senior author Professor David Silver used molecular modeling and biochemical analyses of altered Mfsd2a transporters to derive a structural model of human Mfsd2a. Importantly, the work identifies new binding features of the transporter, providing insight into the transport mechanism of Mfsd2a.

“Our study provides the first glimpse into what Mfsd2a looks like and how it might transport essential lipids across the blood-brain barrier,” said Ms Quek. “It also facilitates a structure-guided search and design of scaffolds for drug delivery to the brain via Mfsd2a, or of drugs that can be directly transported by Mfsd2a.”

Currently this information is being used by Duke-NUS researchers to design novel therapeutic agents for direct drug delivery across the blood brain barrier for the treatment of neurological diseases. This initiative by the Centre for Technology and Development (CTeD) at Duke-NUS, is one of many collaborative research efforts aimed at translating Duke-NUS’ research findings into tangible commercial and therapeutic applications for patients.

Ms Quek plans to further validate her findings by purifying the Mfsd2a protein in order to further dissect how it functions as a transporter.

Major Facilitator Superfamily Domain containing 2A (Mfsd2a) was recently characterized as a sodium-dependent lysophosphatidylcholine (LPC) transporter expressed at the blood-brain barrier endothelium. It is the primary route for importation of docosohexaenoic acid and other long-chain fatty acids into foetal and adult brain, and is essential for mouse and human brain growth and function. Remarkably, Mfsd2a is the first identified MFS family member that uniquely transports lipids, implying that Mfsd2a harbours unique structural features and transport mechanism. Here, we present three 3D structural models of human Mfsd2a derived by homology modelling using MelB- and LacY-based crystal structures, and refined by biochemical analysis. All models revealed 12 transmembrane helices and connecting loops, and represented the partially outward-open, outward-partially occluded, and inward-open states of the transport cycle. In addition to a conserved sodium-binding site, three unique structural features were identified: A phosphate headgroup binding site, a hydrophobic cleft to accommodate a hydrophobic hydrocarbon tail, and three sets of ionic locks that stabilize the outward-open conformation. Ligand docking studies and biochemical assays identified Lys436 as a key residue for transport. It is seen forming a salt bridge with the negative charge on the phosphate headgroup. Importantly, Mfsd2a transported structurally related acylcarnitines but not a lysolipid without a negative charge, demonstrating the necessity of a negative charged headgroup interaction with Lys436 for transport. These findings support a novel transport mechanism by which LPCs are flipped within the transporter cavity by pivoting about Lys436 leading to net transport from the outer to the inner leaflet of the plasma membrane.

Brain and eye contain membrane phospholipids that are enriched in the omega-3 fatty acid docosohexaenoic acid (DHA). It is widely accepted that DHA is important for brain and eye function and brain development (1,2), although mechanisms for DHA function in these tissues are not well defined. The mechanism by which DHA and other conditionally essential and essential fatty acids cross the blood-brain barrier (BBB) has been a long-standing mystery. Recently, we identified Major Facilitator Superfamily Domain containing 2a (Mfsd2a, aka NLS1) as the primary transporter by which the brain obtains DHA. Importantly, Mfsd2a does not transport unesterified DHA, but transports DHA in the chemical form of lysophosphatidylcholine (LPC) that are synthesized by the liver and circulate largely on albumin (3). This is consistent with biochemical evidence that the brain does not transport unesterified fatty acids (4) and that LPC is the preferred carrier of DHA to the brain (5,6). Mfsd2a is a sodium-dependent transporter that is part of the Major Facilitator Superfamily (MFS) of proteins. Members of this family with elucidated structures have 12 transmembrane domains composed of two evolutionarily duplicated 6 transmembrane units (7). Transporting an LPC is a unique feature of Mfsd2a, since most members of this family transport water-soluble and minimally polar substrates such as sugars (GLUT, MelB, LacY), and amino acids (TAT1). Mfsd2a transport is not limited to LPCs containing DHA, as it can transport LPCs containing a variety of fatty acyl chains, with higher specificity for LPCs with unsaturated fatty acyl chains with a minimum chain length of 14 carbons (6,8). Crystal structures have been solved for more than a dozen members of the MFS family, with more than 19 structures, including that of Melibiose permease (MelB) of S. typhimurium (9), Lactose permease (LacY) of Escherichia coli (10), glycerol-3-phosphate transporter of E. coli (11) and the mammalian glucose transporters 1, 3, and 5 (GLUT1, GLUT3, GLUT5) (12-14). A common transport mechanism has emerged from both biochemical and structural analyses of MFSs, in which they transport via a rocker-switch, alternating access mechanism (7,15). In the rocker-switch model, rigid-body relative motion of the N- and C-termini domains renders the substrate-binding site alternatively accessible from either side of the membrane.

Mfsd2a is highly expressed at the bloodbrain barrier in both mouse and human (6,16). Mfsd2a deficient mice (KO) have significantly reduced brain DHA as a result of a 90% reduction in brain uptake of LPC containing DHA as well as other LPCs. The most prominent phenotype of Mfsd2a KO mice is microcephaly, and KO mice additionally exhibit motor dysfunction, and behavioral disorders including anxiety and memory and learning deficits (6). In line with the mouse KO phenotypes, human patients with partially or completely inactivating mutations in Mfsd2a presented with severe microcephaly, intellectual disability, and motor dysfunction (8,16). Plasma LPCs are significantly elevated in both KO mice and human patients with Mfsd2a mutations, consistent with reduced uptake at the blood-brain barrier. Taken together, these findings demonstrate that LPCs are essential for normal brain development and function in mouse and humans.

The fact that Mfsd2a transports a lysolipid, a non-canonical substrate for an MFS protein, might indicate unique structure features and a novel transport mechanism. However, no structural information or mechanism of transport of Mfsd2a is known. Human Mfsd2a is composed of 530 amino acids, with two glycosylation sites at Asn217 and Asn227. Mfsd2a is evolutionarily conserved from teleost fish to humans. Although not a functional ortholog of bacterial MFS transporters, Mfsd2a shares 25% and 26% amino acid sequence identity with S. typhimurium MelB (9,17), and LacY from E. coli (10), respectively. Given the high conservation of the MFS fold, the use of homology modeling to gain insight into the structure of S. typhimurium MelB, for example, has proven to be highly accurate and largely consistent with subsequent X-ray crystal data (9,18). Here, we take advantage of two recently derived high resolution X-ray crystal structures of S. typhimurium MelB (9), and a high resolution X-ray crystal structure of LacY (10) to generate three predictive structural models of human Mfsd2a. These models reveal three unique regions critical for function – an LPC headgroup binding site, a hydrophobic cleft occupied by the LPC fatty acyl tail, and three sets of ionic locks. These structural features indicate a novel mechanism of transport for LPCs.

Mfsd2a is a sodium-dependent lysophosphatidylcholine transporter essential for human brain growth and function (40). Mfsd2a is the only known MFS member or secondary transporter that transports a lipid. In line with its unique function, the current study has identified three unique structural features based on a combination of homology structural modeling and biochemical analysis – (1) a unique headgroup binding site and (2) a hydrophobic cleft for acyl chain binding, and (4) 3 sets of ionic locks that stabilize the outward open conformation. Drawing together these findings with studies of the mechanism of transport of other MFS family members, we propose the following alternatingaccess mechanism for LPC transport (Fig. 6). In the first steps, LPC inserts itself into the outer leaflet of the membrane and diffuses laterally into the transporter’s hydrophobic cleft. As Mfsd2a undergoes conformational changes from the outward open to the inward open conformation, the zwitterionic headgroup is inverted from the outer membrane leaflet to the inner membrane leaflet along a translocation pathway within the transporter, interacting with specific polar and charged residues lining the path. Since LPCs are hydrophobic phospholipids, it is unlikely that they will partition out of the transporter into the aqueous environment of the cytoplasm. We propose that the “flipped” LPC exits the transporter laterally into the membrane environment of the inner leaflet. This model of LPC flipping requires further biochemical proof. Of particular interest is the visualization of the interaction of the negatively charged phosphate headgroup of LPC with Lys436 that is maintained in both outward and inward open conformations. The sidechain of Lys436 is seen to be pointing in the upward direction in the outward open conformation, but pointing downward into the translocation cleft in the inward open conformation. These findings suggest that the Lys436 acts as a tether to push or pivot the headgroup down into the translocation cavity while the N- and C-termini of Mfsd2a rock and switch from outward to inward open.

Interestingly, Lys436 is orthologous to the residue Lys377 in the melibiose transporter of S. typhimurium. Based on the S. typhimurium MelB crystal structure, Lys377 has been predicted to be involved in binding melibiose, and in forming a hydrogen bond with Tyr120, likely separating the sodium binding site from the central hydrophilic cavity (9). In a recent molecular dynamic simulation of E. coli MelB, Lys377 was noted to interact differently with residues involved in the sodium binding site (Asp55, Asp59, and Asp124) in the presence or absence of a sodium ion, and thought to be critical for the spatial organization of the sodium binding site (41). Similarly, in our refined models of Mfsd2a, Lys436 is localized in close proximity to the sodium-binding site residue, Asp93, and the central translocation pathway where it has been identified by docking studies to interact with the charged headgroup of LPC. We hypothesize that Lys436 may shuttle between the two binding sites, communicating and coordinating the occupancy status of the two sites. Interestingly, there is a distinct mobility shift in Mfsd2a bands on SDS-PAGE between wild-type Mfsd2a and the L-3 mutant (R498E, R499E, R500E, K503E, K504E) (Fig. 5I) that is not seen when each of the residues are mutated individually (Fig. S1). These findings are consistent with a conformational change in the L-3 mutant. Given that the L-3 ionic lock is visualized in the outward partially occluded model, we hypothesize that the loss of the L-3 ionic lock results in Mfsd2a being trapped in an energetically more favorable inward open conformation, resulting in the loss of transport function (Fig. 5H).

Patients with the partially inactivating mutation p.(S399L) exhibited significant increases specifically in plasma LPCs having monounsaturated (18:1 – 92%, p=0.004) and polyunsaturated LPCs (18:2, 20:4, 20:3 – 254%, p=0.002; 117%, p=0.007, and 238%, p=0.002), but not in the most abundant LPCs – saturated LPCs (C16:0, C18:0) (8). This is consistent with a greater specificity of Mfsd2a for LPCs with unsaturated fatty acyl chains (6)…A possible explanation for this acyl chain specificity is related to the mobility of the acyl tail in the membrane. It is known that phospholipids with unsaturated fatty acyl chains disrupt the packing of the bilayer, resulting in greater lateral membrane fluidity (42). Therefore, one possible mechanism for LPC specificity is that LPCs with unsaturated fatty acyl chains have greater lateral mobility in the membrane, increasing the Ka for interacting with the transport cleft of Mfsd2a.

Another important structural feature of the physiological ligand, LPC, is a minimum acyl chain length of 14 carbons is required for transport by Mfsd2a. A possible explanation for this requirement is that the hydrocarbon chain must extend beyond the cleft, protruding into the hydrophobic milieu of the phospholipid bilayer core. This interaction of the fatty acyl tail with the acyl chains of the membrane bilayer may provide a hydrophobic force strong enough to pull the molecule through and out of the transporter as the LPC headgroup partitions into the inner leaflet of the membrane. A similar scenario is seen in the Sec translocon where a hydrophobic transmembrane domain of a protein partitions laterally from the Sec61p complex channel into the lipid bilayer (43,44). This proposal that the omega carbon of the fatty acyl chain sticks out of the Mfsd2a pocket is consistent with the observation that Mfsd2a can transport nitrobenzoxadiazole (NBD) or Topfluor when these moieties are attached to the omega carbon of the LPC fatty acyl tail [1].

Other known transmembrane phospholipid transporters include flippases, floppases, and scramblases. Flippases and floppases utilize ATP to drive the uphill transport of aminophospholipids from the outer to the inner leaflet, and specific substrates from the inner to the outer leaflet, respectively (45-47). Scramblases are less well understood, facilitating transport of substrates in either direction down concentration gradients upon activation. While the substrates are similar, several differences make comparisons between Mfsd2a and phospholipid transporters of limited relevance. First, the shapes of the substrates differ in shape and size – lysophospholipids are smaller and conical while phospholipids are cylindrical. Second, unlike flippases and floppases, Mfsd2a is a secondary transporter, utilizing a sodium electrochemical gradient to drive the transport of lysophospholipids from one leaflet to the other. Third, the overall structure of MFS members is different from P4- ATPases and ABC transporters. Consequently, the mechanism of action between Mfsd2a and flippases such as P4-ATPases and ABC transporters, or floppases is expected to differ.

Being expressed at the blood-brain barrier, Mfsd2a is a potential conduit for drug delivery to the brain. The blood-brain barrier is highly impermeable, protecting the brain from bloodderived molecules, pathogens, and toxins. However, its impermeability poses a challenge for pharmacological treatment of brain diseases. It has been predicted that 98% of small molecule drugs are excluded from the brain by the blood-brain barrier (48). Currently, most drugs used to treat brain diseases are lipid soluble small molecules with a molecular weight of less than 400 Da (49). A small number of drugs traverse the blood-brain barrier by carrier-mediated transport. An example of this is Levodopa, a treatment for Parkinson’s Disease, which is a precursor of the neurotransmitter dopamine. Levodopa is transported across the blood-brain barrier by the large neutral amino acid transporter, LAT1 (50). Our findings here provide a further refinement of understanding of the structure-activity relationship of LPCs to their transport, and educates the search and design of drugs that can be transported by Mfsd2a. Candidates for transport, whether as a drug itself or as a LPC scaffold, must have a zwitterionic headgroup, but not necessarily a phosphate, and a minimal threshold of hydrophobic character. As the binding pocket is several times larger than LPC, it is sterically feasible to attach a small molecule drug onto LPC or LPC-like scaffolds for delivery across the blood-brain barrier.

In summary, these studies represent a first structural model of human Mfsd2a based on homology modeling and biochemical interrogation. We expect that this model will serve as a foundation for the future development of X-ray crystal structures of the protein, which would provide further insight into the structure and function of this physiologically important transporter required for human brain growth and function.

Scientists in Spain report finding that breast cancer cells need to take up lipids from the extracellular environment so that they can continue to proliferate. The main protein involved in this process is LIPG, an enzyme found in the cell membrane and without which tumor cell growth is arrested. Analyses of more than 500 clinical samples from patients with various kinds of breast tumors reveal that 85% have high levels of LIPG expression.

The research (“FoxA and LIPG Endothelial Lipase Control the Uptake of Extracellular Lipids for Breast Cancer Growth”) is published in Nature Communications.

In Spain, breast cancer is the most common tumor in women and the fourth most common type in both sexes (data from the Spanish Society of Medical Oncology, 2012), registering more than 25,000 new diagnoses each year. According to figures from the World Health Organization, every year 1.38 million new cases of breast cancer are diagnosed and 458,000 people die from this disease (International Agency for Research on Cancer Globocan, 2008).

It was already known that cancer cells require extracellular glucose to grow and that they reprogram their internal machinery to produce greater amounts of lipids. The relevance of this study is that it reveals for the first time that tumor cells must import extracellular lipids to grow.

“This new knowledge related to metabolism could be the Achilles heel of breast cancer,” explains ICREA researcher and Institute for Research in Biomedicine–Barcelona group leader Roger Gomis, Ph.D., co-leader of the study together with Joan J. Guinovart, Ph.D., director of IRB Barcelona and professor at the University of Barcelona. Using animal models and cancer cell cultures, the scientists have demonstrated that blocking of LIPG activity arrests tumor growth.

“What is promising about this new therapeutic target is that LIPG function does not appear to be indispensable for life, so its inhibition may have fewer side effects than other treatments,” explains the first author of the study, Felipe Slebe, a Ph.D. Fellow at IRB Barcelona.

According to Dr. Guinovart, “because LIPG is a membrane protein, it is potentially easier to design a pharmacological agent to block its activity.”

“If a drug were found to block its activity, it could be used to develop more efficient chemotherapy treatments that are less toxic than those currently available,” adds Dr. Gomis.

The scientists are now looking into international collaborations for developing LIPG inhibitors.

FoxA and LIPG endothelial lipase control the uptake of extracellular lipids for breast cancer growth

The mechanisms that allow breast cancer (BCa) cells to metabolically sustain rapid growth are poorly understood. Here we report that BCa cells are dependent on a mechanism to supply precursors for intracellular lipid production derived from extracellular sources and that the endothelial lipase (LIPG) fulfils this function. LIPG expression allows the import of lipid precursors, thereby contributing to BCa proliferation. LIPG stands out as an essential component of the lipid metabolic adaptations that BCa cells, and not normal tissue, must undergo to support high proliferation rates. LIPG is ubiquitously and highly expressed under the control of FoxA1 or FoxA2 in all BCa subtypes. The downregulation of either LIPG or FoxA in transformed cells results in decreased proliferation and impaired synthesis of intracellular lipids.

FoxA1 and FoxA2 in BCa growth

The importance of FoxA1 in BCa cells differentiation and its contribution to controlling the expression of metabolic genes in several other tissues makes this transcription factor a highly attractive target to explain the metabolic alterations reported in BCa. For these reason, we decided to ascertain the metabolic processes controlled by FoxA1 in BCa. We first confirmed the association between high FoxA1 expression (mRNA and protein) and luminal subtype (Fig. 1a). To this end, we used two cohorts of primary breast tumours with annotated clinical features and follow-up. The MSKCC/EMC BCa data set is based on gene expression profiles from an original series of 560 cases10, whereas the Spanish BCa data set (n=439) is a tissue microarray of formalin-fixed paraffin-embedded stage I–III breast tumour specimens11 (details provided in Methods Section). High FoxA1 gene expression significantly correlated with high expression of well-established luminal markers, such as GATA3 and ESR1, in primary tumours (Supplementary Fig. 1a). Next we explored FoxA1 expression beyond the luminal subtype. Lower FoxA1 expression was observed in non-luminal tumours (Fig. 1a,b); however, a subset also expressed higher FoxA1 levels (Supplementary Fig. 1b and Supplementary Table 1). Given that FoxA2, in conjunction with FoxA1, is also involved in the regulation of several metabolic pathways, we determined the expression of this factor in BCa samples. Unfortunately, no FoxA2 probes in the Affymetrix platform used in the MSKCC/EMC data set provided a reliable interpretation. To overcome this limitation, we used tissue arrays of early BCa samples (Spanish BCa set). Histological examination of FoxA2-stained tissue microarray slides from the Spanish BCa set revealed the expression of this factor in six non-luminal samples, which were scored as FoxA1− (examples in Fig. 1b and summarized inSupplementary Table 1). Collectively, the number of FoxA+ BCa samples detected by immunohistochemistry accounted for 81.3% of all samples in the Spanish BCa set (Supplementary Table 1), which represent a significant proportion of BCa and point to the participation of FoxA in this disease, beyond to its involvement in differentiation and control of hormonal responses.

(a, top) FoxA1 mRNA expression in the MSKCC/EMC set. BCa samples were stratified in Luminal A, Luminal B, Her2, triple negative and unknown subgroups. The unknown group represents specimens that were not classified in any group. (bottom) FoxA1 protein levels by IHC staining in Luminal, Her2 and triple negative samples in the Spanish BCa set (cohort of 439 BCa patients). Data is average±s.d. (b) FoxA1 and FoxA2 IHC staining in FFPE human specimens representative of the different BCa subtypes. Six independent cases are depicted. FoxA1 and FoxA2 are expressed mainly in the nuclei of tumour cells. Scale bar, 50μm. (c) FoxA1 and FoxA2 mRNA expression analysis by qRT-PCR and protein expression by western blot in human BCa cell lines compared with HMECs. T-test was used. Data are average±s.e.m.; n= 3. Of note, MDA435 are of melanoma origin. (d) FoxA1 and FoxA2 expression in MCF7, MDA231 and their derivatives cells by qRT-PCR and western blot. FoxA1 and FoxA2 depletion was achieved with a doxycycline-inducible short hairpin vector. FoxA-depleted cells were rescued by expression of FoxA2 in MCF7 cells or FoxA1 in MDA231 cells. Cell populations were cultured in the presence or absence of doxycycline for 6 days. P value is the result of T-test. Data are average±s.e.m.;n=3. *P≤0.05, ***P≤0.001 (e, left) Schematic representation of MDA231 and MCF7 cells grown without doxycycline and inoculated in Balb/c nude mice treated with or without doxycycline to induce the expression of the indicated FoxA short hairpins. All tumour cell lines have GFP constitutive expression, and tRFP concomitantly with the short hairpin were expressed in doxycycline treated tumours. (right) Tumour growth of the indicated cell populations inoculated in Balb/c nude mice are determined at the indicated time points. P value is the result of T-test. Data are average±s.e.m.; n= 5–8 tumours. *P≤0.05,**P≤0.01, ***P≤0.001. FFPE, formalin-fixed paraffin-embedded.

Next, we extended our analysis to BCa cell lines for further mechanistic studies. We compared FoxA1 and FoxA2 mRNA expression in four estrogen receptor positive (ER+) (MCF7, T47D, BT474 and ZR75) and four estrogen receptor negative (ER−) (SKBR3, MDA468, BT20 and MDA231) BCa cell lines, a cell line of melanoma origin (MDA435), and human mammary epithelial cells (HMECs). Of note, two of the BCa lines tested were HER2+ (BT474 and SKBR3) (Fig. 1c). All ER+ BCa cells (MCF7, T47D, BT474 and ZR75), the ER−/HER2+ SKBR3 and both triple negative-like MDA468 and BT20 cell lines expressed FoxA1. Interestingly, MDA231 triple negative-like cells expressed high levels of FoxA2 but not FoxA1, and the non-tumour HMECs did not express these factors (Fig. 1c). No BCa cells co-expressed these two proteins (Fig. 1c). Our results suggest that the expression of FoxA transcription factors is a common feature of breast tumours, as well as of BCa cell lines. This notion implies that FoxA factors play a major role in BCa growth, independently of luminal fate specification.

To examine the molecular basis of the contribution of FoxA1 and FoxA2 to BCa growth, we engineered constitutive GFP-luciferase-expressing MCF7 and MDA231 cells with a doxycycline-inducible short-hairpin RNA (sh-RNA) vector targeting either FoxA1 or FoxA2. Doxycycline addition to the cell culture media decreased FoxA expression in both cell lines compared with control cells (ShControl (Dox+) and Sh FoxA1 or Sh FoxA2 (Dox−))(Fig. 1d), with the concomitant expression of tRFP (Supplementary Fig. 1c). Of note, there was no gain of expression of FoxA2 in FoxA1-depleted cells or vice versa (Fig. 1d). Interestingly, cancer cell proliferation was impaired in vitroupon depletion of either FoxA1 or FoxA2 in MCF7 and MDA231 cells, respectively (Supplementary Fig. 1d,e). Similarly, when Balb/c nude mice implanted with xenograft tumours from the above described cellular populations were treated with doxycycline and the short hairpins were induced, striking differences in tumour growth were observed. FoxA1-depleted MCF7 and FoxA2-depleted MDA231 tumour growth was blunted (Fig. 1e and additional controls in Supplementary Fig. 1f. Experimental details in the Supplementary Methods Section). Collectively, these observations confirm that FoxA1 or FoxA2 expression is required for BCa growth.

Previous studies indicate that FoxA1 and FoxA2 transcriptionally regulate common genes in the liver and pancreas that are central to development and metabolism. We therefore hypothesized that crossed expression of FoxA factors could rescue tumour growth by restoring the expression of essential metabolic genes. To this end, we engineered doxycycline-driven shFoxA1 MCF7 cells to express exogenous FoxA2 and doxycycline-driven shFoxA2 MDA231 cells to express exogenous FoxA1 (Fig. 1d). Interestingly, when these BCa modified cells were implanted in Balb/c nude mice and FoxA depletion was induced with doxycycline, the sustained expression of another FoxA factor (FoxA2 in MCF7 and FoxA1 in MDA231 cells) was sufficient for tumours to continuously grow (Fig. 1e and additional controls in Supplementary Fig. 1f). Quantitative real-time PCR (qRT-PCR) analysis confirmed FoxA expression in the distinct tumour populations ex-vivo (Supplementary Fig. 1g). These results showed that retention of minimal levels of FoxA1 or FoxA2 expression is necessary for BCa cell growth.

FoxA1- and FoxA2-regulated transcripts for BCa growth

Figure 2: A genomic approach to identify FoxA1- and FoxA2-regulated transcripts in MCF7 and MDA231 cells.

(a) FACS profiling of MCF7 and MDA231 cells derived from tumours isolated from mice on the basis of the expression of GFP+ and RFP− (control group) or GFP+ and tRFP+ (knockdown and rescue groups). (b) Representation of the transcripts up- and downregulated by FoxA in MCF7 and MDA231 cells isolated from tumours. Up- and downregulated transcripts present a Bayesian false discovery rate below 5% and fold change >2.5. (c) LIPG, Bcl2 and Cdh11OB mRNA levels of the indicated genetically modified MCF7 and MDA231 tumour xenografts analysed by qRT-PCR. P value is the result of T-test. Data are average±s.e.m.; n= 5–8 tumours. *P≤0.05, ***P≤0.001. (d) LIPG protein expression in constitutive shFoxA1 MCF7 or shFoxA2 MDA231 cells. (e) Promoter reporter assay in HEK 293 cells. Cells were transfected with LIPG promoter reporter and FoxA1 or FoxA2 expressing vectors when indicated. P value is the result of T-test. Data are average±s.e.m.; n=3. ****P≤0.0001.

LIPG expression in BCa

Next, we showed that LIPG expression in primary tumours was specific to BCa tumour cells and not to other stroma cellular entities (Fig. 3a). Subsequently, we tested LIPG expression in normal breast epithelia and interrogated 20 samples from mammoplasty reductions. Normal breast epithelial cells showed a lower expression of LIPG than cells from tumour specimens (Fig. 3b). Similar results were obtained for LIPG protein levels in a panel from BCa lines compared with HMEC cells. Of the cellular populations tested, the eight BCa cell lines expressing FoxA1 or FoxA2 had very high levels of LIPG protein compared with the melanoma MDA435 cell line and the human epithelial cell (Fig. 3c). Consistent with this observation, 83.8% of BCa samples in the Spanish tumour cohort were LIPG+ (Fig. 3d and Supplementary Table 3), and LIPG expression correlated with FoxA expression (Spearman correlation; r=0.477, P=0.000001; Fig. 3e). Further analysis showed that LIPG expression levels in primary tumours do not have the capacity to stratify patients for differential risk of overall or disease-free survival (Supplementary Fig. 2a) and are not dependent on estrogen signalling (Supplementary Fig. 2b), thus reinforcing the notion that LIPG is essential for BCa growth.

a) Representative LIPG IHC staining on primary BCa tissues (cohort of 439 BCa patients). LIPG is expressed in the cytoplasm of tumour cells. Faint staining is also detected in the extracellular area. Scale bar, 50μm. (b) Representative LIPG IHC staining in normal breast tissue from mammoplasty reductions. Weak LIPG expression occurs in epithelial cells from ducts and lobuli. Scale bar, 50μm. (c) LIPG protein expression in human cancer cell lines compared with HMECs. Actin was used as loading control.*Unspecific band. Of note, MDA435 are of melanoma origin. (d) LIPG protein levels by IHC staining in Luminal, Her2, and triple negative samples in the Spanish BCa set (cohort of 439 BCa patients). Data is average±s.d. (e) Spearman correlation (P=0.000001) between FoxA and LIPG IHC staining intensities in Spanish BCa set (cohort of 439 BCa patients). (f) Left panel, in vitro proliferation curves of MCF7 and MDA231 cells transduced with a control or a LIPG short hairpin. Data are average±s.e.m.; n=3. (right) LIPG protein expression in shLIPG MCF7 and shLIPG MDA231 cells. The blot shown is representative of three independent experiments. P value is the result of T-test.**P≤0.01, ***P≤0.001. (g) Tumour growth of the indicated cell populations inoculated in Balb/c nude mice are determined at the indicated time points.P value is the result of T-test. Data are average±s.e.m.; n= 6–8 tumours. *P≤0.05.

LIPG is a phospholipase located in the cytosol and cellular membrane and has been shown to hydrolyse extracellular phospholipids from high-density lipoprotein that are afterwards incorporated into intracellular lipid species thus providing lipid precursors of cell metabolism17, 18. Thus we questioned whether LIPG regulates essential lipid intake in BCa and whether it is necessary for proliferation. To validate this hypothesis, we genetically downregulated the expression of this protein in MCF7 and MDA231 cells by means of sh-RNA (Fig. 3f and Supplementary Fig. 2c). LIPG depletion blunted BCa cell capacity to proliferate in vitro (Fig. 3f), as previously observed in FoxA-depleted cells (Supplementary Fig. 1d,e), and caused a reduction in invasion and self-renewal properties (Supplementary Fig. 3a–d). Similarly, LIPG-depleted cells were unable to grow tumours in vivo (Fig. 3g).

LIPG location has been shown to be functional on the outer face of the cellular membrane (Fig. 4a)18, thus we postulated the possibility that BCa cells are dependent on LIPG function to access extracellular lipids to support their growth needs. To test this notion, we profiled the media of control and LIPG-depleted MCF7 and MDA231 cells following the same liquid chromatography-mass spectrometry-based untargeted lipidomic approach as for cell homogenates. LIPG depletion prevented the absorption of particular lipids from the media (Supplementary Fig. 4a). The structural identification of the lipids by MS/MS confirms the absence of degradation of glycerophospholipids belonging to the LPC class in both MCF7 and MDA231 cells, which is depicted by higher levels in the media of these species in LIPG-depleted when compared with control cells (Fig. 4d,e). Interestingly when we analysed the LPCs species in the media of control and LIPG-depleted cells and compared with fresh media (without cells), all LPC species from control cell media were decreased. This reduction was weaker in the media of Sh LIPG cells, indicating that LIPG-depleted cells have a defect in processing and importing of pre-existing lipid species from the medium (Fig. 4f).

Finally, we evaluated which of the commonly identified potential substrates of LIPG sustains BCa cell proliferation. Initially, we confirmed that the growth of MCF7 and MDA231 cells is impaired when grown in vitro in lipoprotein-depleted media (Fig. 4g). Next we tested the capacity of LPC (18:0) to rescue BCa cell growth in the absence of lipoproteins and confirmed that this lysophosphatidylcholine was able to restore the cells’ capacity to proliferate (Fig. 4g). In accordance, this process was dependent on LIPG expression (Fig. 4g). Similarly, LIPG-depleted cells were not able to grow in vivo in animals fed with high-fat diet (Fig. 4h) indicating that LIPG is indispensable to process the extracellular lipids and mediate their uptake by the cells, irrespectively of the concentration of lipid substrates in circulation, a phenotype also observed in FoxA-depleted cells (Fig. 4h).

(a, top) Homology 3D structural model of LIPG (backbone coloured according to the QMEANlocal parameter values; red residues with low error). The heavy atoms of the three catalytic residues are shown explicitly and the residue mutated in this study is shown in green (Asp 193). (b) FoxA1, FoxA2 and LIPG protein expression in MCF7, MDA231 and their derivative cells determine by western blot. FoxA1 and FoxA2 depletion was achieved with a doxycycline-inducible short hairpin vector. FoxA-depleted cells were rescued by expression of a WT or Inactive LIPG. Cell populations were cultured in the presence or absence of doxycycline for 6 days. *blots represent different exposition times. (c) Tumour growth of the indicated cell populations inoculated in Balb/c nude mice are determined at the indicated time points. Pvalue is the result of T-test. Data are average±s.e.m.; n=5–8 tumours. *P≤0.05, **P≤0.01. (d) MDA231 and MCF7 cell growth for 48h treated with DMSO (control), FAS inhibitor (C75) and/or lipase inhibitor (Orlistat). For MDA231 cells C75 was used at a final concentration of 10μgml−1 and for MCF7 cells 8μgml−1. Orlistat was used at a final concentration of 30 or 10μgml−1 in MCF7 or MD231 respectively. Pvalue is the result of T-test. Data are average±s.e.m.; n=3.*P≤0.05, **P≤0.01, ***P≤0.001. (e) Forty-eight hours cell growth of MDA231 or MCF7 cells overexpressing exogenous WT or Inactive LIPG. Cells were treated with DMSO (control) and FAS inhibitor (C75) at a final concentration of 20μgml−1. P value is the result of T-test. Data are average±s.e.m.; n=3.***P≤0.001, ****P≤0.0001 (f) Schematic representation showing how FoxA controls LIPG and lipid metabolism to support tumour growth.

As previous reports showed that de novo lipid metabolism is necessary for BCa growth3, 22, we next questioned whether this lipid synthesis was sufficient or, instead, whether exogenous sources are also required to support BCa cell growth and proliferation, as suggested by our experimental data. To this end, we inhibited the activity of fatty acid synthase (FAS) in BCa cells by means of the chemical inhibitor C75 (ref. 23). FAS activity is crucial for de novo lipid synthesis in cancer cells3,22. To test the complementarity of both de novo and/or exogenous lipid supplies, we used a C75 concentration causing a 50% reduction in BCa cell growth in vitro 48h post incubation (Fig. 5d andSupplementary Fig. 5d). Similarly, we tested the contribution of LIPG inhibition by means of treatment with a lipase inhibitor, Orlistat21. A specific dose causing a 50% reduction in the growth of each BCa cell line was further used (Fig. 5d and Supplementary Fig. 5d). Interestingly, concomitant treatment with FAS and LIPG inhibitors caused an additive effect, blunting BCa cell growth (Fig. 5d). Next, we evaluated whether LIPG activity was sufficient to rescue the chemical inhibition of FAS. To this end, we overexpressed WT and inactive LIPG and grew MCF7 and MDA231 cells in the presence or absence of a high dose of C75 (20mgml−1), which blocks cell growth (Supplementary Fig. 5d). Complete blockade of FAS was not rescued by LIPG (Fig. 5e). Collectively, our results suggest that both exogenous lipid precursors provided by means of LIPG activity and de novo lipid synthesis mediated by FAS are necessary for BCa cell growth.

Here we reveal that FoxA factors provide a central metabolic growth function by specifically regulating LIPG expression, thereby allowing the acquisition of indispensable extracellular lipids for BCa tumour proliferation. FoxA family of transcription factors are expressed in the vast majority of BCa and FoxA1 is expressed across various BCa subtypes. Moreover we show that, in some cases, its absence is associated with the expression of FoxA2. Interestingly, in addition of FoxA1 contribution to luminal commitment24, 25, 26, 27 the factor may drive BCa growth by specifically regulating LIPG levels.

The catalytic activity of LIPG generates extracellular lipid precursors that are imported to fulfill the intracellular production of lipid species (Fig. 5f). LIPG downregulation blocks BCa cell growth, thereby indicating that the import of extracellular lipid precursors is important for the proliferation of these cells. This is a striking observation given that it is generally believed that de novo fatty acid synthesis is the main driver of tumour growth22. Indeed, our experimental data with LIPG-depleted BCa cells revealed a massive decrease of most intracellular glycerolipid intermediates in the synthesis of TG (PC, PE, PG and DG) and their derivatives (LPC and LPE). Accordingly, certain lipid species (LPC) in the media were not decreased in LIPG-depleted cells as much as in control cells, thus indicating that extracellular lipids are the substrates for intracellular lipid production. In particular, we demonstrate the relevance of extracellular LPC (18:0) for BCa cell proliferation in a lipoprotein-depleted medium, a process dependent on LIPG. In this context, a high-fat diet was shown to rescue the absence of a critical intracellular lipase, Monoacylglycerol lipase, for cancer pathogenesis given cancer cells ability to uptake lipids from the extracellular compartment was functional19. Herein, we showed that this rescue mechanism is not functional in BCa cells in the absence of FoxA2 or LIPG. In support of this notion, it is worth noting that extracellular LIPG activity releases fatty acids from high-density lipoprotein phospholipids and these acids are further employed for intracellular lipid production in the human hepatic cell line HepG2 (refs 28, 29).

In conclusion, BCa cells are dependent on a mechanism to supply precursors derived from extracellular sources for intracellular lipid production, and LIPG fulfills this function. Therefore, LIPG stands out as an important component of the lipid metabolic adaptations that BCa cells, and not normal tissue, must undergo to support high proliferation rates. Our results also suggest thatde novo lipid synthesis is necessary but not sufficient to support lipid production for BCa tumour growth. Accordingly, recent clinical studies demonstrate the association between lipids and lipoproteins in circulation and risk of BCa in women with extensive mammographic density. This observation implies that interventions aimed to reduce them may have effect on BCa risk30. All together, these observations make LIPG activity an Achilles heel of luminal and, more importantly, of triple negative/basal-like breast tumours, for which limited therapeutic options are currently available.

In normal cells, the glucose carbon flow is directed into a de novo lipogenic pathway that is regulated, in part, via phosphoinositide-3 kinase (PI-3K)-dependent activation of ATP citrate lyase (ACL), a key rate-limiting, enzyme in de novo lipogenesis. ACL is a cytosolic enzyme that catalyzes the generation of acetyl CoA from citrate. Inhibition of ACL results in a loss of B-cell growth and cell viability [10] .
The plasma membrane and its constituent phosphoinositides form the basis of the phosphatidylinositol 3-kinase (PI3-K) signaling pathway, which is crucial for cell proliferation and survival. Phosphatase and tensin-homolog deleted on chromosome 10 (PTEN) is a tumor-suppressor protein that regulates phosphatidylinositol 3-kinase (PI3-K) signaling by binding to the plasma membrane and hydrolyzing the 3′ phosphate from phosphatidylinositol (3,4,5)-trisphosphate (PI(3,4,5)P3) to form phosphatidylinositol (4,5)-bisphosphate (PI(4,5)P2). Several loss-of-function mutations in PTEN that impair lipid phosphatase activity and membrane binding are oncogenic, leading to the development of a variety of cancers. Of these three residues, R335 was observed to interact with the membrane to the greatest extent across all of the simulations. R335L, in common with several other germline mutations, has been associated with the inherited cancer [11] .
ACLY is up-regulated or activated in several types of cancers, and its inhibition is known to induce proliferation arrest in cancer cells both in vitro and in vivo. The last studies were showed that BCR-mediated signaling is regulated in part by the amount of membrane cholesterol. It was observed that statins (Lovostatin), the pharmacological inhibitors of cholesterol synthesis, induce apoptosis of CLL cells in vitro and in vivo. Also the ectopic expression of CD5 in a B-cell line stimulates the transcription of genes involved in the synthesis of cholesterol [12] .

In 2005, David Lyden noticed something unexpected. He and his colleagues at Weill Cornell Medical College had been researching metastasis—the spread of cancer from one part of the body to another. The team had shown that bone marrow–derived cells (BMDCs) were recruited to future metastatic sites before the arrival of tumor cells, confirming that metastasis occurred after a habitable microenvironment, or “premetastatic niche,” had been prepared.1

But carefully studying images of this microenvironment in the lung tissue of mice, Lyden saw something else. Amongst the BMDCs, the micrographs showed tiny specks, far too small to be cells, gathering at the future site of metastasis. “I said, ‘What are these viruses doing here?’” recalls Lyden. “I had no idea about exosomes, microvesicles, and microparticles.”

Those specks, Lyden would come to realize, were in fact primary tumor–derived exosomes. These membrane-enclosed vesicles packed full of molecules are now attracting growing attention as important mediators of intercellular communication, particularly when it comes to cancer’s insidious capacity to spread from one organ to another.

Preparing the ground

Tumors require a community of support cells, including fibroblasts, BMDCs, and endothelial cells, to provide functional and structural assistance and to modulate immune system behavior. Bringing together the first members of this community before the arrival of tumor cells is all part of cancer’s survival strategy, says Joshua Hood, a cancer researcher at the University of Louisville.

“It wouldn’t be efficient for tumor cells to strike out on their own, and just say, ‘Oh, here we are!’” he says. “They would run the risk of being destroyed.” Preparing a “nest” in advance makes the process much safer. “Then the tumor can just efficiently come along and set up shop without ever having to fight much of a battle with the immune system.”

But although Lyden’s group had shown that this preparation was taking place, it remained unclear how such a process might be regulated. For the next few years, many cancer researchers believed that tumor cells must communicate with the premetastatic niche primarily through tumor-secreted signaling molecules such as cytokines.

Meanwhile, research into extracellular vesicles, previously considered biological garbage bags, was revealing new modes of intercellular communication. In 2007, a group of scientists in Sweden discovered that exosomes, tiny vesicles measuring just 30 nanometers to 100 nanometers across, transport mRNA and microRNAs intercellularly, with the potential to effect changes in protein synthesis in recipient cells.2 A new means for tumors to regulate distant cellular environments came into focus, and research on exosomes exploded. In 2011, Hood and his colleagues showed that exosomes facilitate melanoma metastasis through the lymphatic system.3 The following year, Lyden’s group demonstrated that tumor-derived exosomes can direct BMDCs to one of melanoma’s most common sites of metastasis, the lung.4 Exosomes, it seemed, had been underestimated.

Tiny terraformers

Armed with the knowledge that exosomes are involved in multiple stages of melanoma metastasis, Lyden’s lab went searching for the vesicles’ potential role in the metastasis of other cancers. Turning to pancreatic ductal adenocarcinoma (PDAC)—one of the most lethal cancers in humans—postdoctoral researcher Bruno Costa-Silva led a series of exhaustive in vitro and in vivo experiments in mouse models to detail the process of premetastatic niche formation in the liver, PDAC’s most common destination. The team’s results, published last May, reveal an intricate series of sequential steps—mediated by PDAC-derived exosomes (Nature Cell Biol, 17:816-26, 2015).

Using fluorescence labeling, Lyden’s group observed that PDAC-derived exosomes are taken up by Kupffer cells, specialized macrophages lining the outer walls of blood vessels in the liver. There, the exosomes trigger the cells’ secretion of transforming growth factor β (a type of cytokine involved in cell proliferation), plus the production of fibronectin by neighboring hepatic stellate cells, and the recruitment of BMDCs.

The researchers also showed that this cascade of events could be inhibited by depleting exosomal macrophage migratory inhibitory factor (MIF), an abundant protein in PDAC exosomes. “If you target the specific proteins of exosomes, you can reduce metastasis,” explains coauthor Héctor Peinado, leader of the microenvironment and metastasis group at the Spanish National Cancer Research Center.

For Hood, the findings add to a developing picture of exosomes’ vital role as “vanguard” in the progression of cancer. “It’s like the colonization of a new planet,” he says. “They’re terraforming the environment to make it hospitable.”

Although research was revealing the steps involved in forming premetastatic sites, it was less clear how these sites were being selected. “This has always been a great mystery in cancer,” says Ayuko Hoshino, a research associate in Lyden’s lab. “Why do certain cancers metastasize to certain organs?”

One theory, proposed in 1928 by pathologist James Ewing, suggested that anatomical and mechanical factors explained organ specificity in metastasis. The premetastatic niche, then, might form wherever exosomes are likely to land. But this couldn’t be the whole story, says Hoshino. “For instance, there’s eye melanoma. Thinking about that site, you could imagine it metastasizing to the brain. But actually, it almost only metastasizes to the liver.”

Because exosomes arrive at metastatic sites before tumor cells, the team reasoned, perhaps the exosomes themselves were organotropic (i.e., attracted to particular organs or tissues). Sure enough, Lyden says, when Hoshino and Costa-Silva began injecting tumor-derived exosomes into mice, “their preliminary findings were that wherever they injected the exosomes, the pancreatic cancer ones were ending up in the liver and the breast metastasis exosomes would end up in the lung.”

Using mass spectrometry, the researchers analyzed the protein content of exosomes from lung-tropic, liver-tropic, and brain-tropic tumors. They found that the composition of exosomes’ integrins—membrane proteins involved in cell adhesion—was destination-specific (Nature, 527:329-35, 2015). Exosomes bearing integrin α6β4, for example, were directed to the lung, where they could prepare a premetastatic niche potent enough even for normally bone-tropic tumor cells to colonize. Integrin αvβ5, meanwhile, directed metastasis to the liver.

The researchers also showed that exosomal integrins didn’t necessarily correspond to the parent-cell proteins, making exosomes potentially better indicators of where a cancer will spread than the tumor cells themselves. “We can show that an integrin that’s high in the tumor cell might be completely absent in the tumor exosome or vice versa,” says Lyden, adding that, taken together, the results point to a role for exosomes in “dictating the future sites of metastasis.”

“It’s a beautiful story,” says Dihua Yu, a molecular and cellular oncologist at the University of Texas MD Anderson Cancer Center. “This is a very novel finding that gives really good indicators for potential strategies to intervene in metastasis.”

Metastatic crosstalk

In the same month that Lyden’s group published its work on organotropism, Yu’s own lab published a different exosome study—one that told another side of the story.

Yu and her colleagues had found that when tumor cells in mice metastasized to the brain, they downregulated expression of a tumor suppressor gene called PTEN, and became primed for growth at the metastatic site. When the tumor cells were taken out of the microenvironment and put in culture, however, they restored normal PTEN expression.

The researchers demonstrated that a microRNA from astrocytes—star-shape glial cells in the brain—reversibly downregulated the levels of PTEN transcripts in the tumor cells, but they couldn’t figure out how the microRNA was getting into the tumor. Blocking “obvious signaling pathways,” such as gap junctions, failed to have an effect, Yu says.

Scrutinizing astrocyte-conditioned media using electron microscopy, the researchers identified spherical vesicles between 30 nanometers and 100 nanometers in diameter—the defining size of exosomes. Exposing mouse tumor cells to these vesicles increased cell microRNA content and reduced PTENexpression (Nature, 527:100-04, 2015). The study revealed yet another role for exosomes in the communication between tumors and their microenvironment.

The findings were a surprise, says Yu, not least because they showed a different perspective from the bulk of recent research. “We’re talking about astrocytes in the brain secreting exosomes to give welcome help to the cancer cells,” she says.

“I find it an extremely interesting paper because it shows that the astrocytes can change the whole phenotype of the tumor in the brain,” says Lyden. He adds that the results underline the importance of studying the mutational status of tumors at various sites. “All this work in exosomes, it adds to the complexity,” he says. “We can’t just target tumor cells at the primary site. We’ll have to understand all the details of metastasis if we’re really going to tackle it.”

What’s next?

The discovery of multiple roles for exosomes in metastasis has generated excitement about the potential for their use in diagnostics and treatment. As protective containers of tumor-derived genetic material, exosomes could provide information about the status of cancer progression. And as mediators of premetastatic niche formation, they make obvious targets for inhibition. (See “Banking on Blood Tests,”here.)

Exosomes might even be useful as vehicles to deliver drugs because they’re patient-matched and “naturally designed to function in a biocompatible way with living systems,” says Hood. “You could take them out of people, and at some point down the road try to have patients be their own nanofactory, using their own particles for treatment purposes.”

Pancreatic ductal adenocarcinomas (PDACs) are highly metastatic with poor prognosis, mainly due to delayed detection. We hypothesized that intercellular communication is critical for metastatic progression. Here, we show that PDAC-derived exosomes induce liver pre-metastatic niche formation in naive mice and consequently increase liver metastatic burden. Uptake of PDAC-derived exosomes by Kupffer cells caused transforming growth factor β secretion and upregulation of fibronectin production by hepatic stellate cells. This fibrotic microenvironment enhanced recruitment of bone marrow-derived macrophages. We found that macrophage migration inhibitory factor (MIF) was highly expressed in PDAC-derived exosomes, and its blockade prevented liver pre-metastatic niche formation and metastasis. Compared with patients whose pancreatic tumours did not progress, MIF was markedly higher in exosomes from stage I PDAC patients who later developed liver metastasis. These findings suggest that exosomal MIF primes the liver for metastasis and may be a prognostic marker for the development of PDAC liver metastasis.

The development of life-threatening cancer metastases at distant organs requires disseminated tumour cells’ adaptation to, and co-evolution with, the drastically different microenvironments of metastatic sites1. Cancer cells of common origin manifest distinct gene expression patterns after metastasizing to different organs2. Clearly, the dynamic interaction between metastatic tumour cells and extrinsic signals at individual metastatic organ sites critically effects the subsequent metastatic outgrowth3, 4. Yet, it is unclear when and how disseminated tumour cells acquire the essential traits from the microenvironment of metastatic organs that prime their subsequent outgrowth. Here we show that both human and mouse tumour cells with normal expression of PTEN, an important tumour suppressor, lose PTEN expression after dissemination to the brain, but not to other organs. The PTEN level in PTEN-loss brain metastatic tumour cells is restored after leaving the brain microenvironment. This brain microenvironment-dependent, reversible PTEN messenger RNA and protein downregulation is epigenetically regulated by microRNAs from brain astrocytes. Mechanistically, astrocyte-derived exosomes mediate an intercellular transfer of PTEN-targeting microRNAs to metastatic tumour cells, while astrocyte-specific depletion of PTEN-targeting microRNAs or blockade of astrocyte exosome secretion rescues the PTEN loss and suppresses brain metastasis in vivo. Furthermore, this adaptive PTEN loss in brain metastatic tumour cells leads to an increased secretion of the chemokine CCL2, which recruits IBA1-expressing myeloid cells that reciprocally enhance the outgrowth of brain metastatic tumour cells via enhanced proliferation and reduced apoptosis. Our findings demonstrate a remarkable plasticity of PTEN expression in metastatic tumour cells in response to different organ microenvironments, underpinning an essential role of co-evolution between the metastatic cells and their microenvironment during the adaptive metastatic outgrowth. Our findings signify the dynamic and reciprocal cross-talk between tumour cells and the metastatic niche; importantly, they provide new opportunities for effective anti-metastasis therapies, especially of consequence for brain metastasis patients.

No matter where a tumor lurks in the body, its secrets circulate in the blood. Stray tumor cells begin metastatic migrations by slipping into the vasculature. Vesicles secreted by cancer cells and free-floating DNA are also released into the bloodstream. Because these bits of cellular debris are a grab-bag of biomarkers that could both signal a cancer’s presence and predict its progression and response to treatment, the use of blood-based tests, or liquid biopsies, to detect and evaluate them is now drawing significant commercial interest.

Last year, San Diego–based Pathway Genomics began advertising a screen “for the early detection of up to 10 different cancer types in high-risk populations.” But the screen had only been tested in already-diagnosed patients, not in at-risk individuals, and within weeks of making it commercially available, the company received an FDA notice to provide more information about their promotional claims before further marketing. “We . . . have not found any published evidence that this test or any similar test has been clinically validated as a screening tool for early detection of cancer in high risk individuals,” the agency wrote.

Ahelium balloon tugs gently at the end of its string. The tension in the string resists the buoyant force of the helium, and the elastic nature of the balloon’s rubber contains the helium gas as it tries to expand. Cutting the string or poking the rubber with a pin reveals the precarious balance between the forces, upsets the equilibrium, and sets the system into motion.

Some biological tissues also exist in such a state of offsetting forces. The most familiar example is the balance between blood pressure and the elastic tension in the cardiovascular system that contains and conveys blood without bursting or collapsing. And in tumors, both solid and fluid forces are generated that make the cancerous tissue a lot like that helium balloon: cut a tumor with a scalpel and it rapidly swells and deforms as pent-up forces break free from structural elements that are severed.1

One force that is notably higher in tumors than in healthy tissues is fluid pressure, resulting from hyperpermeable, leaky blood vessels and a dearth of draining lymphatic vessels. Researchers have known since the 1950s that tumors exhibit elevated fluid pressure, but the implications for tumor progression and drug delivery were not realized until the late 1980s. That was when we (R.K.J. and colleagues) used a mathematical model to predict—and subsequently validate in animal and human tumors—that a precipitous drop in fluid pressure at the tumor–normal tissue interface causes interstitial fluid to ooze out of the tumor.2 This seeping fluid pushes drugs, growth factors, and cancer cells into the surrounding tissue and lymphatics, reducing drug delivery and facilitating local tumor invasion and distant metastasis.

Based on this insight, we suggested in 2001 that anti-angiogenic drugs could be used to lower a tumor’s fluid pressure and improve treatment outcome.3 This hypothesis changed the thinking about how existing anti-angiogenesis therapies actually work and spurred research into other physical forces acting in cancer.4 In the last 15 years, researchers have identified diverse sources of increased pressure in tumors, which may serve as possible targets for cancer therapy.5 For example, solid forces exerted by the extracellular matrix can be reduced by treatment with drugs approved by the US Food and Drug Administration (FDA) for controlling hypertension (angiotensin blockers) or diabetes (metformin). Retrospective clinical studies have found improved survival in cancer patients who were treated with these agents, which are now being tested in prospective trials for a variety of solid tumors.6,7

Tumors under pressure

In vitro experiments showing that cancer cells actively migrate in response to fluid flow have supported the hypothesis that fluid escaping from the boundary of a tumor may guide the invasive migration of cancer cells toward lymphatic or blood vessels, potentially encouraging metastasis. There remains controversy over how the fluid forces induce the migration; the cells may respond to chemical gradients created by the cells and distorted by the flowing fluid,8 or the fluid may activate cell mechanosensors.9 Because of the potential for new therapeutic interventions, the transduction of mechanical fluid forces into biochemical signals by cell mechanosensors is an active area of investigation. In a more direct manner, the fluid flow can physically carry cancer cells to lymph nodes.

Fluid forces may also promote tumor progression by recruiting blood vessels into the cancerous mass.10 Because tumor blood vessels are leaky, plasma can pass freely between vessels that have different pressures. When this happens at the periphery of a tumor, where angiogenic growth factors are prevalent, there can be synergistic induction of new vessel sprouts.

And fluid pressure is just one of the many forces in a tumor that can influence its development and progression. Tumors also develop increased solid pressure, as compared with normal tissue, stemming from the uncontrolled division of cancer cells and from the infiltration and proliferation of stromal and immune cells from the surrounding tissue and circulation. High-molecular-weight polysaccharides known as hydrogels found in the extracellular matrix (ECM) also add pressure on a tumor. The most well-studied of these hydrogels is hyaluronan; when the polysaccharide absorbs water, it swells, pressing on surrounding cells and structural elements of the tissue.

The ECM contains a highly interconnected network of collagen and other fibers and is normally very good at resisting and containing such tension. It also has support from infiltrating myofibroblasts, which detect areas where the ECM density or tension is not normal and initiate actomyosin-based contraction of collagen and elastin matrix structures to restore tensional homeostasis. But while this repair effort is typically effective in healthy tissues, uncooperative tumor cells interfere with these efforts, both by themselves generating pressure and by hyperactivating cancer-associated fibroblasts to produce more ECM and thus produce even more force.11

Because cell growth and ECM composition are not spatially uniform in cancer, tumors are subjected to multiple, dispersed sources of pressure associated with matrix “containers” of various sizes. This solid pressure from within the tumor deforms the surrounding normal tissue, potentially facilitating the metastatic escape of cancer cells. The physical forces also compress blood vessels and lymphatic vessels in the tumor and adjacent normal tissue,12 increasing the fluid pressure in the tumor13 and interrupting the delivery of nutrients, removal of waste, and entry of tumor-targeted drugs via the blood.4 Insufficient blood flow also results in poor oxygenation, which has been linked to immunosuppression, inflammation, invasion, and metastasis, as well as lowered efficacy of chemo-, radio-, and immunotherapies.4 These are all indirect consequences of solid stresses in and on tumors.

Such forces can also have direct effects on cancer cells, and may serve as independent triggers for tumor invasion. Mechanical forces are central to many of our sense systems, such as hearing, touch, and pain, and to tissue maintenance programs, such as bone regeneration and blood vessel remodeling. In these systems, mechanical forces are transduced by mechanosensors to activate downstream biochemical and genetic pathways. (See “Full Speed Ahead,” The Scientist, December 2009.) Cancer cells may similarly be able to sense and respond to dynamic forces in tumors. We have shown, for example, that metastatic cancer cells exposed to compressive stresses in a culture dish undergo a phenotypic transformation to become more invasive,14 and others have shown that compressive forces applied in vivo can also induce oncogenes in normal epithelium of the mouse colon.15

It is thus becoming quite clear that the physical environment can influence a tumor’s development and spread, and it may even be possible for physical forces to kick-start cancerous growth.

…..

Full Speed Ahead

Physical forces acting in and around cells are fast—and making waves in the world of molecular biology.

When it comes to survival, few things are more important than being able to respond quickly to a change of circumstances. And when it comes to fast-acting indicators, it turns out that signals induced by physical forces acting in and around cells, appropriately dubbed biomechanical signals, are the champions of the cellular world.

“If you look at this mechanical signaling, it’s about 30 meters per second—that’s very fast,” says bioengineer Ning Wang of the University of Illinois at Urbana-Champaign. That’s faster than most family-owned speedboats, and second only to electrical (e.g., nerve) impulses in biological signaling. By comparison, small chemicals moving by diffusion average a mere 2 micrometers per second—a speed even the slowest row boater could easily top.

Indeed, when the two signal types were pitted against each other in a cellular race last year, the mechanical signals left chemical signals in their wake, activating proteins at distant sites in the cytoplasm in just a fraction of a second, at least 40 times faster than their growth factor opponent.1 Mechanical signals are so fast, Wang adds, they are “beyond our resolution,” meaning that current imaging techniques cannot capture the very first cellular changes that result from mechanical stress, which occur within nanoseconds.

For centuries, scientists have scrutinized the molecular inner workings of the body, with little or no regard to the physical environment in which these biological reactions take place. But the growing realization that physical forces have a pervasive presence in physiology (operating in a variety of bodily systems in thebone, blood, kidney, and ear, for instance), and act with astonishing speed, has caused many to consider the possibility that mechanical signaling may be just as important as chemical communication in the life of a cell.

“Biologists have traditionally ignored the role of mechanics in biology,” says biomechanical engineer Mohammad Mofrad of the University of California, Berkley, “[but] biomechanics is becoming increasingly accepted, and people are recognizing its role in development, in disease, and in general cellular and tissue function.”

The wave within: Mechanical forces acting inside the cell

Once believed to be little more than sacks of chemically active goop, cells didn’t seem capable of transmitting physical forces into their depths, and researchers largely limited their search for molecules or structures that respond to physical forces, or mechanosensors, to the plasma membrane.

Mechanical signaling may be just as important as chemical communication in the life of a cell.

In the late 1990s, however, closer examination revealed that the cell’s interior is in fact a highly structured environment, composed of a network of filaments.2 Pull on one side of the cell, and these filaments will transmit the force all the way to other side, tugging on and bumping into a variety of cellular structures along the way—similar to how a boat’s wake sends a series of small waves lapping up on a distant and otherwise peaceful shoreline. Scientists are now realizing the potential of such intracellular jostling to induce molecular changes throughout the cell, and the search for mechanosensing molecules has escalated dramatically in scope, including, for example, several proteins of the nucleus.

It’s a search that will likely last a while, predicts cell biologist Donald Ingber, director of the Wyss Institute for Biologically Inspired Engineering at Harvard University. “To try to find out what’s the mechanosensor is kind of crazy at this point,” he says. As scientists are now learning, “the whole cell is the mechanosensor.”

A key player, most agree, is the cytoskeleton, which is comprised of a variety of microfilaments, including rigid actin filaments and active myosin motors—the two principle components of muscle. Activation of the so-called nonmuscle myosins causes the cytoskeleton to contract, much like an arm muscle does when it lifts a heavy object.

The first intimation that the cytoskeleton could go beyond its established inner-cell duties (molecule transport and cell movement and division) came in 1997, when Ingber did the logical (in hindsight, at least) experiment of pulling on the cells to see what happened inside.2 Using a tiny glass micropipette coated in ligands, Ingber and his team gently probed the surface proteins known as integrins, which secure the cell to the extracellular matrix. When they quickly pulled the micropipette away, they saw an immediate cellular makeover: cytoskeletal elements turned 90 degrees, the nucleus distorted, and the nucleolus—a small, dense structure within the nucleus that functions primarily in ribosome assembly—aligned itself with the direction of the applied force.

“That kind of blew people away,” Ingber recalls. “It revealed that cells have incredible levels of structure not only in the cytoplasm but in the nucleus as well.”

Wang (once a postdoc in Ingber’s lab at the Harvard School of Public Health) and other collaborators combined a similar technique with fluorescent imaging technology to visualize how these forces were channeled within the cell’s interior. Upping the resolution and further refining these techniques, Wang began mapping these intracellular forces as they made their way through the cell. In 2005, the maps confirmed the physical connection between the cell-surface integrins and the nucleus, and showed that these external forces follow a nonrandom path dictated by the tension of the cytoskeletal elements.3

“Biomechanics is becoming increasingly accepted, and people are recognizing its role in development, in disease, and in general cellular and tissue function.”
–Mohammad Mofrad

The end point of these mechanical pathways is likely a mechanosensitive protein, which changes shape in response to the force, thereby exposing new binding areas or otherwise changing the protein’s function. In mitochondria, for example, mechanical forces may trigger the release of reactive oxygen species and activation of signaling molecules that contribute to inflammation and atherosclerosis.

Similarly, proteins on the nuclear membrane may pass mechanical signals into the nucleus by way of a specialized structure known as LINC (linker of nucleoskeleton and cytoskeleton), which physically links the actin cytoskeleton to proteins important in nuclear organization and gene function. To determine if mechanical forces directly affect gene expression, last year scientists began exploiting the increasingly popular fluorescence resonance energy transfer (FRET) technology,1 in which energy emitted by one fluorescent molecule can stimulate another, resulting in a visible energy transfer that can track enzymatic activities in live cells. By combining FRET technology with the techniques that apply physical forces to specific cell membrane proteins, scientists can visualize entire mechanochemical transduction pathways, Wang says.

“The big issue right now in the field of mechanotransduction is whether the genes in the nucleus can be directly activated by forces applied to the cell surface,” Wang explains. While the physical maps of the cytoskeleton tentatively sketch out a path that supports this possibility, confirmatory data is lacking. This combination of new technologies will be “tremendously” helpful in answering that question, he says, and “push the field” towards a more complete understanding of how mechanical forces can influence cellular life.

An early start: Mechanical forces in development

In the world of developmental biology, the cytoskeleton’s role in biomechanics really comes into its own. As the embryo develops, the cells themselves are the force generators, and by contracting at critical times, the cytoskeleton can initiate many key developmental steps, from invagination and gastrulation to proliferation and differentiation, and overall cellular organization.

The idea that physical forces play a role in development is not a new one. In the early 20th century, back when Albert Einstein was first developing the molecular basis of viscosity and scientists were realizing molecules are distinct particles, biologist and mathematician D’Arcy Thompson of the University of Dundee in Scotland suggested that mechanical strain is a key player in morphogenesis. Now, nearly a century later, biologists are finally beginning to agree.

Because Thompson “couldn’t measure [the forces] at that time, that kind of thinking got pushed to the wayside as genetic thinking took over biology,” says bioengineer Christopher Chen of the University of Pennsylvania. That is, until 2003, when Emmanuel Farge of the Curie Institute in France squeezedDrosophila embryos to mimic the compression experienced during early development and activated twist—a critical gene in the formation of the digestive tract.4 These results gave weight to Thompson’s idea that stress in the embryo stimulates development and growth, and inspired developmental scientists to begin considering mechanical effects, Chen says. “Now we’re at the stage where there’s a lot of interest and willingness to consider the fact that mechanical forces are not only shaping the embryo, but are linked to the differentiation programs that are going on.”

Again, the cytoskeleton is a key player in this process. In fruit flies and frogs, for example, nonmuscle myosins contract the actin filaments to generate the compressive forces necessary for successful gastrulation—the first major shape-changing event of development. Myosins similarly influence proliferation in the development of the Drosophila egg chamber, with increased myosin activity resulting in increased cell division.

Cytoskeleton contractility also appears to direct stem cell differentiation. In 2006, Dennis Discher of the University of Pennsylvania demonstrated that the tension of the substrate on which cells are grown in culture is important for determining what type of tissue the cells will form.5 Cells grown on soft matrices that mimic brain tissue tended to grow into neural cells, while cells grown on stiffer matrices grew into muscle cell precursors, and hard matrices yielded bone. In this case, it seems that stiffer substrates increased the expression of nonmuscle myosin, generating greater tension in the actin cytoskeleton and affecting differentiation. (Altering or inhibiting myosin contraction can also affect differentiation.)

“To try to find out what’s the mechanosensor is kind of crazy at this point. As scientists are now learning, the whole cell is the mechanosensor.”
–Donald Ingber

……..

Shaping a tumor

In addition to the influence of physical forces on cancer growth and invasion, forces can alter a tumor’s mechanical properties, and vice versa. Tumors are more rigid, or stiffer, than surrounding tissues, usually because they contain excess collagen in the ECM,5 and this can contain and amplify local forces produced by proliferating cancer cells. On the other hand, tumor rigidity can be further enhanced if the cells exert tension on ECM collagen fibers by pulling on them, or by stretching them, as occurs when tumors grow uncontrollably. Fluid forces can also influence the assembly of collagen fibers within and around tumors,8potentially increasing stiffness.

Importantly, tumor stiffness tends to be associated with poor prognoses, though the reasons for this are not fully understood. Cells are known to differentiate into different lineages depending on the local rigidity;16 for example, stem cells differentiate into bone on stiff substrates, but make adipose (fat) cells on softer substrates. Similar mechanisms are thought to affect tumor progression when the ECM changes rigidity, inducing cancer cells to become more invasive as well as more likely to metastasize. Indeed, longer collagen fibers in the matrix are associated with increased invasion and metastasis, as well as reduced survival, in mice.17

In addition, the abnormal ECM in tumors can affect cancer progression by activating normal stromal cells, such as macrophages and fibroblasts, that accelerate tumor growth and treatment resistance. These activated stromal cells further strengthen and stretch the ECM, causing a snowball effect.

The biochemical composition and organization of the ECM also influences tumor biology. Dysregulation of normal matrix signals can lead to tumor progression, characterized by excessive cell proliferation, immortality, enhanced migration, changes in metabolism, and evasion of the immune response. More research is needed to dissect the relationships between the ECM’s mechanical properties, forces, and cell signaling pathways.

Targeting the ECM

Because unchecked proliferation of cancer cells increases solid stress in the tumor, anticancer therapies should decrease the compressive forces in tumors and reopen collapsed blood and lymphatic vessels.11 This is exactly what happens when tumors are treated with certain doses of paclitaxel or docetaxel, two widely used cancer drugs. Shrinking tumors increases blood flow and allows more efficient fluid movement through the extravascular space, lowering the tumor interstitial fluid pressure in mouse models and in patients with breast cancer.5 However, cancer cells invariably develop resistance to treatment and begin to regrow, increasing solid stress again. As a result, other targets for reducing solid stresses are needed.

Because of its role in containing and concentrating the forces in a tumor, the collagen matrix within and around the tumor is another potential target for relieving tumor-related stresses. Indeed, solid stress in tumors can be reduced by drugs that selectively reprogram activated fibroblasts or modify the assembly of matrix components such as collagen and hyaluronan. In rodent studies, targeting these force-altering components in the tumor microenvironment has been shown to decrease solid stress, improve blood perfusion and drug delivery, and improve tumor response to chemotherapy and animal survival.6 We have found, for example, that injecting tumors with a collagen-digesting enzyme increases the diffusion of antibodies and viral particles and improves drug penetration in the tumor. Similarly, treatments that target transforming growth factor–beta (TGF-β), which controls the production of collagen by myofibroblasts, increase perfusion, improve the delivery of drugs of all sizes in mammary tumors, and improve treatment outcomes in mice.5

A class of drugs that is widely used to control blood pressure in hypertensive patients also blocks the TGF-β pathway. These drugs, known as angiotensin receptor 1 blockers, can reduce collagen production in and around the tumor by reducing the activity of TGF-β, as well as by blocking the function of connective tissue growth factor (CTGF), which is involved in stabilizing collagen and inducing resistance to chemotherapy.6Losartan and other angiotensin inhibitors reduce levels of collagen in various experimental models of fibrosis, and decrease renal and cardiac fibrosis in hypertensive patients. When given to mice with one of four different types of tumors characterized by high levels of cancer-associated fibroblasts (CAFs) and excess extracellular matrix—pancreatic ductal adenocarcinoma, breast cancer, sarcoma, and melanoma—losartan treatment caused a decrease in collagen content in a dose-dependent manner, enhanced penetration of nanoparticles into the tumor, and improved efficacy of diverse anticancer drugs. This is supported by a number of retrospective studies in patients with pancreatic, lung, and kidney cancers.6Researchers at Massachusetts General Hospital are now running a Phase 1/2 clinical trial to test losartan in pancreatic cancer patients.

Another potential cancer treatment target is hyaluronan, which is abundant in 20 percent to 30 percent of human tumors, most notably breast, colon, and prostate cancers. In addition to its role as a pressure-creating gel, hyaluronan can sequester growth factors and inhibit interstitial fluid movement within the tumor. Hyaluronidase, an enzyme that digests hyaluronan, reduces mechanical stress in tumors grown in mice.1 And San Diego–based Halozyme Therapeutics’s PEGPH20, a formulation of hyaluronidase coated with polyethylene glycol to enhance bioavailability, can decompress blood vessels and improve treatment outcome in genetically engineered mouse models of pancreatic ductal adenocarcinoma. Based on these studies, Halozyme researchers are now testing PEGPH20 in a randomized clinical trial of pancreatic cancer patients. Another matrix-altering drug is the widely-prescribed antidiabetic drug metformin, which has been shown to decrease collagen and hyaluronan levels in pancreatic tumors in obese mice and patients.7 Metformin is currently being tested in more than 200 clinical trials worldwide as a treatment for different types of cancer.

Clearly, tumors should be studied not only in light of their biochemical processes and genetic underpinnings, but also for the specific physical forces and mechanical properties that may influence progression. Understanding the physical microenvironment of tumors, as well as its interplay with the biochemical environment, is necessary to improve cancer detection, prevention, and treatment.

Illustration depicting a biocell attached to a CMOS integrated circuit with a membrane containing sodium-potassium pumps in pores. Energy is stored chemically in ATP molecules. When the energy is released as charged ions (which are then converted to electrons to power the chip at the bottom of the experimental device), the ATP is converted to ADP + inorganic phosphate. (credit: Trevor Finney and Jared Roseman/Columbia Engineering)

Columbia Engineering researchers have combined biological and solid-state components for the first time, opening the door to creating entirely new artificial biosystems.

In this experiment, they used a biological cell to power a conventional solid-state complementary metal-oxide-semiconductor (CMOS) integrated circuit. An artificial lipid bilayer membrane containing adenosine triphosphate (ATP)-powered ion pumps (which provide energy for cells) was used as a source of ions (which were converted to electrons to power the chip).

The study, led by Ken Shepard, Lau Family Professor of Electrical Engineering and professor of biomedical engineering at Columbia Engineering, was published online today (Dec. 7, 2015) in an open-access paper in Nature Communications.

How to build a hybrid biochip

Living systems achieve this functionality with their own version of electronics based on lipid membranes and ion channels and pumps, which act as a kind of “biological transistor.” Charge in the form of ions carry energy and information, and ion channels control the flow of ions across cell membranes.

Solid-state systems, such as those in computers and communication devices, use electrons; their electronic signaling and power are controlled by field-effect transistors.

To build a prototype of their hybrid system, Shepard’s team packaged a CMOS integrated circuit (IC) with an ATP-harvesting “biocell.” In the presence of ATP, the system pumped ions across the membrane, producing an electrical potential (voltage)* that was harvested by the integrated circuit.

“We made a macroscale version of this system, at the scale of several millimeters, to see if it worked,” Shepard notes. “Our results provide new insight into a generalized circuit model, enabling us to determine the conditions to maximize the efficiency of harnessing chemical energy through the action of these ion pumps. We will now be looking at how to scale the system down.”

While other groups have harvested energy from living systems, Shepard and his team are exploring how to do this at the molecular level, isolating just the desired function and interfacing this with electronics. “We don’t need the whole cell,” he explains. “We just grab the component of the cell that’s doing what we want. For this project, we isolated the ATPases because they were the proteins that allowed us to extract energy from ATP.”

The capability of a bomb-sniffing dog, no Alpo required

Next, the researchers plan to go much further, such as recognizing specific molecules and giving chips the potential to taste and smell.

The ability to build a system that combines the power of solid-state electronics with the capabilities of biological components has great promise, they believe. “You need a bomb-sniffing dog now, but if you can take just the part of the dog that is useful — the molecules that are doing the sensing — we wouldn’t need the whole animal,” says Shepard.

The technology could also provide a power source for implanted electronic devices in ATP-rich environments such as inside living cells, the researchers suggest.

* “In general, integrated circuits, even when operated at the point of minimum energy in subthreshold, consume on the order of 10−2 W mm−2 (or assuming a typical silicon chip thickness of 250 μm, 4 × 10−2 W mm−3). Typical cells, in contrast, consume on the order of 4 × 10−6 W mm−3. In the experiment, a typical active power dissipation for the IC circuit was 92.3 nW, and the active average harvesting power was 71.4 fW for the biocell (the discrepancy is managed through duty-cycled operation of the IC).” — Jared M. Roseman et al./Nature Communications

There is enormous potential in combining the capabilities of the biological and the solid state to create hybrid engineered systems. While there have been recent efforts to harness power from naturally occurring potentials in living systems in plants and animals to power complementary metal-oxide-semiconductor integrated circuits, here we report the first successful effort to isolate the energetics of an electrogenic ion pump in an engineered in vitro environment to power such an artificial system. An integrated circuit is powered by adenosine triphosphate through the action of Na+/K+ adenosine triphosphatases in an integrated in vitro lipid bilayer membrane. The ion pumps (active in the membrane at numbers exceeding 2 × 106mm−2) are able to sustain a short-circuit current of 32.6pAmm−2 and an open-circuit voltage of 78mV, providing for a maximum power transfer of 1.27pWmm−2 from a single bilayer. Two series-stacked bilayers provide a voltage sufficient to operate an integrated circuit with a conversion efficiency of chemical to electrical energy of 14.9%.

The energetics of living systems are based on electrochemical membrane potentials that are present in cell plasma membranes, the inner membrane of mitochondria, or the thylakoid membrane of chloroplasts1. In the latter two cases, the specific membrane potential is known as the proton-motive force and is used by proton adenosine triphosphate (ATP) synthases to produce ATP. In the former case, Na+/K+-ATPases hydrolyse ATP to maintain the resting potential in most cells.

While there have been recent efforts to harness power from some naturally occurring potentials in living systems that are the result of ion pump action both in plants2 and animals3, 4 to power complementary metal-oxide semiconductor (CMOS) integrated circuits (ICs), this work is the first successful effort to isolate the energetics of an electrogenic ion pump in an engineered in vitroenvironment to power such an artificial system. Prior efforts to harness power from in vitromembrane systems incorporating ion-pumping ATPases5, 6, 7, 8, 9 and light-activated bacteriorhodopsin9, 10, 11 have been limited by difficulty in incorporating these proteins in sufficient quantity to attain measurable current and in achieving sufficiently large membrane resistances to harness these currents. Both problems are solved in this effort to power an IC from ATP in an in vitro environment. The resulting measurements provide new insight into a generalized circuit model, which allows us to determine the conditions to maximize the efficiency of harnessing chemical energy through the action of electrogenic ion pumps.

ATP-powered IC

Figure 1a shows the complete hybrid integrated system, consisting of a CMOS IC packaged with an ATP-harvesting ‘biocell’. The biocell consists of two series-stacked ATPase bearing suspended lipid bilayers with a fluid chamber directly on top of the IC. Series stacking of two membranes is necessary to provide the required start-up voltage for IC and eliminates the need for an external energy source, which is typically required to start circuits from low-voltage supplies2, 3. As shown inFig. 1c, a matching network in the form of a switched capacitor allows the load resistance of the IC to be matched to that presented by the biocell. In principle, the switch S can be implicit. The biocell charges CSTOR until the self start-up voltage, Vstart, is reached. The chip then operates until the biocell voltage drops below the minimum supply voltage for operation, Vmin. Active current draw from the IC stops at this point, allowing the charge to build up again on CSTOR. In our case, however, the IC leakage current exceeds 13.5nA at Vstart, more than can be provided by the biocell. As a result, an explicit transistor switch and comparator (outside of the IC) are used for this function in the experimental results presented here, which are not powered by the biocell and not included in energy efficiency calculations (see Supplementary Discussion for additional details). The energy from the biocell is used to operate a voltage converter (voltage doubler) and some simple inverter-based ring oscillators in the IC, which receive power from no other sources.

…….. Prior to the addition of ATP, the membrane produces no electrical power and has an Rm of 280GΩ. A 1.7-pA short-circuit (SC) current (Fig. 2b) through the membrane is observed upon the addition of ATP (final concentration 3mM) to the cis chamber where functional, properly oriented enzymes generate a net electrogenic pump current. To perform these measurements, currents through each membrane of the biocell are measured using a voltage-clamp amplifier (inset of Fig. 2b) with a gain of 500GΩ with special efforts taken to compensate amplifier leakage currents. Each ATPase transports three Na+ ions from the cis chamber to the trans chamber and two K+ ions from thetrans chamber to the cis chamber (a net charge movement of one cation) for every molecule of ATP hydrolysed. At a rate of 100 hydrolysis events per second under zero electrical (SC) bias13, this results in an electrogenic current of ~16aA. The observed SC current corresponds to about 105 active ATPases in the membrane or a concentration of about 2 × 106mm−2, about 5% of the density of channels occurring naturally in mammalian nerve fibres14. It is expected that half of the channels inserted are inactive because they are oriented incorrectly.

Figure 2a shows the complete measured current–voltage (I–V) characteristic of a single ATPase-bearing membrane in the presence of ATP. The current due to membrane leakage through Rm is subtracted in the post-ATP curve. The I–V characteristic fits a Boltzmann sigmoid curve, consistent with sodium–potassium pump currents measured on membrane patches at similar buffer conditions13, 15, 16. This nonlinear behaviour reflects the fact that the full ATPase transport cycle (three Na+ ions from cis to trans and two K+ ions from trans to cis) time increases (the turn-over rate, kATP, decreases) as the membrane potential increases16. No effect on pump current is expected from any ion concentration gradients produced by the action of the ATPases (seeSupplementary Discussion). Using this Boltzmann fit, we can model the biocell as a nonlinear voltage-controlled current source IATPase (inset Fig. 2a), in which the current produced by this source varies as a function of Vm. In the fourth quadrant, where the cell is producing electrical power, this model can be linearized as a Norton equivalent circuit, consisting of a DC current source (Ip) in parallel with a current-limiting resistor (Rp), which acts to limit the current delivered to the load at increasing bias (IATPase~Ip−Vm/Rp). Figure 2c shows the measured and simulated charging of Cm for a single membrane (open-circuited voltage). A custom amplifier with input resistance Rin>10TΩ was required for this measurement (see Electrical Measurement Methods).

Reconciling operating voltage differences

The electrical characteristics of biological systems and solid-state systems are mismatched in their operating voltages. The minimum operating voltage of solid-state systems is determined by the need for transistors to modulate a Maxwell–Boltzmann (MB) distribution of carriers by several orders of magnitude through the application of a potential that is several multiples of kT/q (where kis Boltzmann’s constant, T is the temperature in degrees Kelvin and q is the elementary charge). Biological systems, while operating under the same MB statistics, have no such constraints for operating ion channels since they are controlled by mechanical (or other conformational) processes rather than through modulation of a potential barrier. To bridge this operating voltage mismatch, the circuit includes a switched-capacitor voltage doubler (Fig. 1d) that is capable of self-startup from voltages as low Vstart=145mV (~5.5kT/q) and can be operated continuously from input voltages from as low as Vmin=110mV (see Supplementary Discussion)…..

Maximizing the efficiency of harvesting energy from ATP

Solid-state systems and biological systems are also mismatched in their operating impedances. In our case, the biocell presents a source impedance, =84.2GΩ, while the load impedance presented by the complete integrated circuit (including both the voltage converter and ring oscillator loads) is approximately RIC=200kΩ. (The load impedance, RL, of the ring oscillators alone is 305kΩ.) This mismatch in source and load impedance is manifest in large differences in power densities. In general, integrated circuits, even when operated at the point of minimum energy in subthreshold, consume on the order of 10−2Wmm−2 (or assuming a typical silicon chip thickness of 250μm, 4 × 10−2Wmm−3) (ref. 17). Typical cells, in contrast, consume on the order of 4 × 10−6Wmm−3 (ref. 18). In our case, a typical active power dissipation for our circuit is 92.3nW, and the active average harvesting power is 71.4fW for the biocell. This discrepancy is managed through duty-cycled operation of the IC in which the circuit is largely disabled for long periods of time (Tcharge), integrating up the power onto a storage capacitor (CSTOR), which is then expended in a very brief period of activity (Trun), as shown in Fig. 3a.

The overall efficiency of the system in converting chemical energy to the energy consumed in the load ring oscillator (η) is given by the product of the conversion efficiency of the voltage doubler (ηconverter) and the conversion efficiency of chemical energy to electrical energy in the biocell (ηbiocell), η=ηconverter × ηbiocell. ηconverter is relatively constant over the range of input voltages at ~59%, as determined by various loading test circuits included in the chip design (Supplementary Figs 1–6). ηbiocell, however, varies with transmembrane potential Vm. η is the efficiency in transferring power to the power ring oscillator loads from the ATP harvested by biocell.

…….

To first order, the energy made available to the Na+/K+-ATPase by the hydrolysis of ATP is independent of the chemical or electric potential of the membrane and is given by |ΔGATP|/(qNA), where ΔGATP is the Gibbs free energy change due to the ATP hydrolysis reaction per mole of ATP at given buffer conditions and NA is Avogadro’s number. Since every charge that passes through IATPase corresponds to a single hydrolysis event, we can use two voltage sources in series with IATPase to independently account for the energy expended by the pumps both in moving charge across the electric potential difference and in moving ions across the chemical potential difference. The dependent voltage source Vloss in this branch fixes the voltage across IATPase, and the total power produced by the pump current source is (|ΔGATP|/NA)(NkATP), which is the product of the energy released per molecule of ATP, the number of active ATPases and the ATP turnover rate. The power dissipated in voltage source Vchem models the work performed by the ATPases in transporting ions against a concentration gradient. In the case of the Na+/K+ ATPase,Vchem is given by . The power dissipated in this source is introduced back into the circuit in the power generated by the Nernst independent voltage sources, and . The power dissipated in the dependent voltage source Vloss models any additional power not used to perform chemical or electrical work. ……

Integration of ATP-harvesting ion pumps could provide a means to power future CMOS microsystems scaled to the level of individual cells22. In molecular diagnostics, the integration of pore-forming proteins such as alpha haemolysin23 or MspA porin24 with CMOS electronics is already finding application in DNA sequencing25. Exploiting the large diversity of function available in transmembrane proteins in these hybrid systems could, for example, lead to highly specific sensing platforms for airborne odorants or soluble molecular entities26, 27. Heavily multiplexed platforms could become high-throughput in vitro drug-screening platforms against this diversity of function. In addition, integration of transmembrane proteins with CMOS may become a convenient alternative to fluorescence for coupling to synthetic biological systems28.

Maintenance of energy homeostasis depends on the highly regulated storage and release of triacylglycerol primarily in adipose tissue and excessive storage is a feature of common metabolic disorders. CIDEA is a lipid droplet (LD)-protein enriched in brown adipocytes promoting the enlargement of LDs which are dynamic, ubiquitous organelles specialized for storing neutral lipids. We demonstrate an essential role in this process for an amphipathic helix in CIDEA, which facilitates embedding in the LD phospholipid monolayer and binds phosphatidic acid (PA). LD pairs are docked by CIDEA trans-complexes through contributions of the N-terminal domain and a C-terminal dimerization region. These complexes, enriched at the LD-LD contact site, interact with the cone-shaped phospholipid PA and likely increase phospholipid barrier permeability, promoting LD fusion by transference of lipids. This physiological process is essential in adipocyte differentiation as well as serving to facilitate the tight coupling of lipolysis and lipogenesis in activated brown fat.

Evolutionary pressures for survival in fluctuating environments that expose organisms to times of both feast and famine have selected for the ability to efficiently store and release energy in the form of triacyclglycerol (TAG). However, excessive or defective lipid storage is a key feature of common diseases such as diabetes, atherosclerosis and the metabolic syndrome (1). The organelles that are essential for storing and mobilizing intracellular fat are lipid droplets (LDs) (2). They constitute a unique cellular structure where a core of neutral lipids is stabilized in the hydrophilic cytosol by a phospholipid monolayer embedding LD-proteins. While most mammalian 46 cells present small LDs (<1 Pm) (3), white (unilocular) adipocytes contain a single giant LD occupying most of their cell volume. In contrast, brown (multilocular) adipocytes hold multiple LDs of lesser size, increasing the LD surface/volume ratio which facilitates the rapid consumption of lipids for adaptive thermogenesis (4).

The exploration of new approaches for the treatment of metabolic disorders has been stimulated by the rediscovery of active brown adipose tissue (BAT) in adult humans (5, 6) and by the induction of multilocular brown-like cells in white adipose tissue (WAT) (7). The multilocular morphology of brown adipocytes is a defining characteristic of these cells along with expression of genes such as Ucp1. The acquisition of a unilocular or multilocular phenotype is likely to be controlled by the regulation of LD growth. Two related proteins, CIDEA and CIDEC promote LD enlargement in adipocytes (8-10), with CIDEA being specifically found in BAT. Together with CIDEB, they form the CIDE (cell death-inducing DFF45-like effector) family of LD-proteins, which have emerged as important metabolic regulators (11).

Different mechanisms have been proposed for LD enlargement, including in situ neutral lipid synthesis, lipid uptake and LD-LD coalescence (12-14). The study of CIDE 62 proteins has revealed a critical role in the LD fusion process in which a donor LD progressively transfers its content to an acceptor LD until it is completely absorbed (15). However, the underlying mechanism by which CIDEC and CIDEA facilitate the interchange of triacylglycerol (TAG) molecules between LDs is not understood. In the present study, we have obtained a detailed picture of the different steps driving this LD enlargement process, which involves the stabilization of LD pairs, phospholipid binding, and the permeabilization of the LD monolayer to allow the transference of lipids.

CIDEA expression mimics the LD dynamics observed during the differentiation of brown adipocytes

Phases of CIDEA activity: LD targeting, LD-LD docking and LD growth

A cationic amphipathic helix in C-term drives LD targeting

The amphipathic helix is essential for LD enlargement

LD-LD docking is induced by the formation of CIDEA complexes

CIDEC differs from CIDEA in its dependence on the N-term domain

CIDEA interacts with Phosphatidic Acid

PA is required for LD enlargement

The Cidea gene is highly expressed in BAT, induced in WAT following cold exposure (46), and is widely used by researchers as a defining marker to discriminate brown or brite adipocytes from white adipocytes (7, 28). As evidence indicated a key role in the LD biology (47) we have characterized the mechanism by which CIDEA promotes LD enlargement, which involves the targeting of LDs, the docking of LD pairs and the transference of lipids between them. The lipid transfer step requires the interaction of CIDEA and PA through a cationic amphipathic helix. Independently of PA-binding, this helix is also responsible for anchoring CIDEA in the LD membrane. Finally, we demonstrate that the docking of LD pairs is driven by the formation of CIDEA complexes involving the N-term domain and a C-term interaction site.

CIDE proteins appeared during vertebrate evolution by the combination of an ancestor N-term domain and a LD-binding C-term domain (35). In spite of this, the full process of LD enlargement can be induced in yeast by the sole exogenous expression of 395 CIDEA, indicating that in contrast to SNARE-triggered vesicle fusion, LD fusion by lipid transference does not require the coordination of multiple specific proteins (48). Whereas vesicle fusion implicates an intricate restructuring of the phospholipid bilayers, LD fusion is a spontaneous process that the cell has to prevent by tightly controlling their phospholipid composition (23). However, although phospholipid-modifying enzymes have been linked with the biogenesis of LDs (49, 50), the implication of phospholipids in physiologic LD fusion processes has not been previously described.

Complete LD fusion by lipid transfer can last several hours, during which the participating LDs remain in contact. Our results indicate that both the N-term domain and a C-term dimerization site (aa 126-155) independently participate in the docking of LD pairs by forming trans interactions (Fig. 7). Certain mutations in the dimerization sites that do not eliminate the interaction result in a decrease on the TAG transference efficiency, reflected on the presence of small LDs docked to enlarged LDs. This suggests that in addition to stabilizing the LD-LD interaction, the correct conformation of the 409 CIDEA complexes is necessary for optimal TAG transfer. Furthermore, the formation of stable LD pairs is not sufficient to trigger LD fusion by lipid transfer. In fact, although LDs can be tightly packed in cultured adipocytes, no TAG transference across neighbour LDs is observed in the absence of CIDE proteins (15), showing that the phospholipid monolayer acts as a barrier impermeable to TAG. Our CG-MD simulations indicate that certain TAG molecules can escape the neutral lipid core of the LD and be integrated within the aliphatic chains of the phospholipid monolayer. This could be a transition state 416 prior to the TAG transference and our data indicates that the docking of the amphipathic helix in the LD membrane could facilitate this process. However, the infiltrated TAGs in LD membranes in the presence of mutant helices, or even in the absence of docking, suggests that this is not enough to complete the TAG transference.

To be transferred to the adjacent LD, the TAGs integrated in the hydrophobic region of the LD membrane should cross the energy barrier defined by the phospholipid polar heads, and the interaction of CIDEA with PA could play a role in this process, as suggested by the disruption of LD enlargement by the mutations preventing PA-binding (K167E/R171E/R175E) and the inhibition of CIDEA after PA depletion. The minor effects observed with more conservative substitutions in the helix, suggests that the presence of positive charges is sufficient to induce TAG transference by attracting anionic phospholipids present in the LD membrane. PA, which requirement is indicated by our PA-depletion experiments, is a cone-shaped anionic phospholipid which could locally destabilize the LD monolayer by favoring a negative membrane curvature incompatible with the spherical LD morphology (51). Interestingly, while the zwitterion PC, the main component of the monolayer, stabilizes the LD structure (23), the negatively charged PA promote their coalescence (29). This is supported by our CD-MD results which resulted in a deformation of the LD shape by the addition of PA. We propose a model in which the C-term amphipathic helix positions itself in the LD monolayer and interacts with PA molecules in its vicinity, which might include trans interactions with PA in the adjacent LD. The interaction with PA disturbs the integrity of the phospholipid barrier at the LD-LD interface, allowing the LD to LD transference of TAG molecules integrated in the LD membrane (Fig. 7). Additional alterations in the LD composition could be facilitating TAG transference, as differentiating adipocytes experience a reduction in saturated fatty acids in the LD phospholipids (52), and in their PC/PE ratio (53) which could increase the permeability of the LD membranes, and we previously observed that a change in the molecular structures of TAG results in an altered migration pattern to the LD surface (32).

During LD fusion by lipid transfer, the pressure gradient experienced by LDs favors TAG flux from small to large LDs (15). However, the implication of PA, a minor component of the LD membrane, could represent a control mechanism, as it is plausible that the cell could actively influence the TAG flux direction by differently regulating the levels of PA in large and small LDs, which could be controlled by the activity of enzymes such as AGPAT3 and LIPIN-1J (13, 30). This is a remarkable possibility, as a switch in the favored TAG flux direction could promote the acquisition of a multilocular phenotype and facilitate the browning of WAT (24). Interestingly, Cidea mRNA is the LD protein- encoding transcript that experiences the greatest increase during the cold-induced process by which multilocular BAT-like cells appear in WAT (24). Furthermore, in BAT, cold exposure instigates a profound increase in CIDEA protein levels that is independent of transcriptional regulation (54). The profound increase in CIDEA is coincident with elevated lipolysis and de novo lipogenesis that occurs in both brown and white adipose tissues after E-adrenergic receptor activation (55). It is likely that CIDEA has a central role in coupling these processes to package newly synthesized TAG in LDs for subsequent lipolysis and fatty acid oxidation. Importantly, BAT displays high levels of glycerol kinase activity (56, 57) that facilitates glycerol recycling rather than release into the blood stream, following induction of lipolysis (58), which occurs in WAT. Hence, the reported elevated glycerol released from cells depleted of CIDEA (28) is likely to be a result of decoupling lipolysis from the ability to efficiently store the products of lipogenesis in LDs and therefore producing a net increase in detected extracellular glycerol. This important role of CIDEA is supported by the marked depletion of TAG in the BAT of Cidea null mice following overnight exposure to 4 °C (28) and our findings that CIDEA-dependent LD enlargement is maintained in a lipase negative yeast strain.

Cidea and the genes that are required to facilitate high rates of lipolysis and lipogenesis are associated with the “browning” of white fat either following cold exposure (46) or in genetic models such as RIP140 knockout WAT (59). The induction of a brown- like phenotype in WAT has potential benefits in the treatment and prevention of metabolic disorders (60). Differences in the activity and regulation of CIDEC and CIDEA could also be responsible for the adoption of unilocular or multilocular phenotypes. In addition to their differential interaction with PLIN1 and 5, we have observed that CIDEC is more resilient to the deletion of the N-term than CIDEA, indicating that it may be less sensitive to regulatory posttranslational modifications of this domain. This robustness of CIDEC activity together with its potentiation by PLIN1, could facilitate the continuity of the LD enlargement in white adipocytes until the unilocular phenotype is achieved. In contrast, in brown adipocytes expressing CIDEA the process would be stopped at the multilocular stage for example due to post-translational modifications that modulate the function or stability of the protein or alteration of the PA levels in LDs.

The myth that diabetes is caused by overeating also hurts the one out of five people who are not overweight when they contract Type 2 Diabetes. Because doctors only think “Diabetes” when they see a patient who fits the stereotype–the grossly obese inactive patient–they often neglect to check people of normal weight for blood sugar disorders even when they show up with classic symptoms of high blood sugar such as recurrent urinary tract infections or neuropathy.

Where Did This Toxic Myth Come From?

The way this myth originated is this: Because people with Type 2 Diabetes are often overweight and because many people who are overweight have a syndrome called “insulin resistance” in which their cells do not respond properly to insulin so that they require larger than normal amounts of insulin to lower their blood sugar, the conclusion was drawn years ago that insulin resistance was the cause of Type 2 Diabetes.

It made sense. Something was burning out the beta cells in these people, and it seemed logical that the something must be the stress of pumping out huge amounts of insulin, day after day. This idea was so compelling that it was widely believed by medical professionals, though few realized it had never been subjected to careful investigation by large-scale research.

That is why any time there is an article in the news about Type 2 Diabetes you are likely to read something that says, “While Type 1 diabetes (sometimes called Juvenile Diabetes) is a condition where the body does not produce insulin, Type 2 Diabetes is the opposite: a condition where the body produces far too much insulin because of insulin resistance caused by obesity.”

When your doctor tells you the same thing, the conclusion is inescapable: your overeating caused you to put on excess fat and that your excess fat is what made you diabetic.

Blaming the Victim

This line of reasoning leads to subtle, often unexpressed, judgmental decisions on the part of your doctor, who is likely to believe that had you not been such a pig, you would not have given yourself this unnecessary disease.

And because of this unspoken bias, unless you are able to “please” your doctor by losing a great deal of weight after your diagnosis you may find yourself treated with a subtle but callous disregard because of the doctor’s feeling that you brought this condition down on yourself. This bias is similar to that held by doctors who face patients who smoke a pack a day and get lung cancer and still refuse to stop smoking.

You also see this bias frequently expressed in the media. Articles on the “obesity epidemic” blame overeating for a huge increase in the number of people with diabetes, including children and teenagers who are pictured greedily gorging on supersized fast foods while doing no exercise more strenuous than channel surfing. In a society where the concepts “thin” and “healthy” have taken on the overtones of moral virtue and where the only one of the seven deadly sins that still inspires horror and condemnation is gluttony, being fat is considered by many as sure proof of moral weakness. So it is not surprising that the subtext of media coverage of obesity and diabetes is that diabetes is nothing less than the just punishment you deserve for being such a glutton.

Except that it’s not true.

Obesity Has Risen Dramatically While Diabetes Rates Have Not

The rate of obesity has grown alarmingly over the past decades, especially in certain regions of the U.S. The NIH reports that “From 1960-2 to 2005-6, the prevalence of obesity increased from 13.4 to 35.1 percent in U.S. adults age 20 to 74.7.”

If obesity was causing diabetes, you’d exect to see a similar rise in the diabetes rate. But this has not happened. The CDC reports that “From 1980 through 2010, the crude prevalence of diagnosed diabetes increased …from 2.5% to 6.9%.” However, if you look at the graph that accompanies this statement, you see that the rate of diabetes diagnoses rose only gradually through this period–to about 3.5% until it suddenly sped upward in the late 1990s. This sudden increase largely due to the fact that in 1998 the American Diabetes Association changed the criteria by which diabetes was to be diagnosed, lowering the fasting blood sugar level used to diagnose diabetes from 141 mg/dl to 126 mg/dl. (Details HERE)

Analyzing these statistics, it becomes clear that though roughtly 65 million more Americans became fat over this period, only 13 million more Americans became diabetic.

And to further confuse the matter, several factors other than the rise in obesity and the ADA’s lowering of the diagnostic cutoff also came into play during this period which also raised the rate of diabetes diagnoses:

Diabetes becomes more common as people age as the pancreas like other organs, becames less efficient. In 1950 only 12% of the U.S. population was over 65. By 2010 40% was, and of those 40%, 19% were over 75.(Details HERE.)

At the same time, the period during which the rate of diabetes rose was also the period in which doctors began to heavily prescribe statins, a class of drugs we now know raises the risk of developing diabetes. (Details HERE.)

Why Obesity Doesn’t Cause Diabetes: The Genetic Basis of Diabetes

While people who have diabetes are often heavy, one out of five people diagnosed with diabetes are thin or normal weight. And though heavy people with diabetes are, indeed, likely to be insulin resistant, the majority of people who are overweight will never develop diabetes. In fact, they will not develop diabetes though they are likely to be just as insulin resistant as those who do–or even more so.

The message that diabetes researchers in academic laboratories are coming up with about what really causes diabetes is quite different from what you read in the media. What they are finding is that to get Type 2 Diabetes you need to have some combination of a variety of already-identified genetic flaws which produce the syndrome that we call Type 2 Diabetes. This means that unless you have inherited abnormal genes or had your genes damaged by exposure to pesticides, plastics and other environmental toxins known to cause genetic damage, you can eat until you drop and never develop diabetes.

Now let’s look in more depth at what peer reviewed research has found about the true causes of diabetes

Twin Studies Back up a Genetic Cause for Diabetes

Studies of identical twins showed that twins have an 80% concordance for Type 2 Diabetes. In other words, if one twin has Type 2 Diabetes, the chance that the other will have it two are 4 out of 5. While you might assume that this might simply point to the fact that twins are raised in the same home by mothers who feed them the same unhealthy diets, studies of non-identical twins found NO such correlation. The chances that one non-identical twin might have Type 2 Diabetes if the other had it were much lower, though these non-identical twins, born at the same time and raised by the same caregivers were presumably also exposed to the same unhealthy diets.

This kind of finding begins to hint that there is more than just bad habits to blame for diabetes. A high concordance between identical twins which is not shared by non-identical twins is usually advanced as an argument for a genetic cause, though because one in five identical twins did not become diabetic, it is assumed that some additional factors beyond the inherited genome must come into play to cause the disease to appear. Often this factor is an exposure to an environmental toxin which knocks out some other, protective genetic factor.

The List of Genes Associated with Type 2 Keeps Growing

Here is a brief list of some of the abnormal genes that have been found to be associated with Type 2 Diabetes in people of European extraction: TCF7L2, HNF4-a, PTPN, SHIP2, ENPP1, PPARG, FTO, KCNJ11, NOTCh3, WFS1, CDKAL1, IGF2BP2, SLC30A8, JAZF1, and HHEX.

People from non-European ethnic groups have been found to have entirely different sets of diabetic genes than do Western Europeans, like the UCP2 polymorphism found in Pima Indians and the three Calpain-10 gene polymorphisms that have been found to be associated with diabetes in Mexicans. The presence of a variation in yet another gene, SLC16A11, was recently found to be associated with a 25% higher risk of a Mexican developing Type 2 diabetes.

The More Diabetes Genes You Have The Worse Your Beta Cells Perform

A study published in the Journal Diabetologia in November 2008 studied how well the beta cells secreted insulin in 1,211 non-diabetic individuals. They then screened these people for abnormalities in seven genes that have been found associated with Type 2 Diabetes.

They found that with each abnormal gene found in a person’s genome, there was an additive effect on that person’s beta cell dysfunction with each additional gene causing poorer beta cell function.

The impact of these genetic flaws becomes clear when we learn that in these people who were believed to be normal, beta cell glucose sensitivity and insulin production at meal times was decreased by 39% in people who had abnormalities in five genes. That’s almost half. And if your beta cells are only putting out half as much insulin as a normal person’s it takes a lot less stress on those cells to push you into becoming diabetic.

What A Common Diabetes Gene Does

A study published in July of 2009 sheds light on what exactly it is that an allele (gene variant) often found associated with diabetes does. The allele in question is one of TCF7L2 transcription factor gene. The study involved 81 normal healthy young Danish men whose genes were tested. They were then given a battery of tests to examine their glucose metabolisms. The researchers found that:

Carriers of the T allele were characterised by reduced 24 h insulin concentrations … and reduced insulin secretion relative to glucose during a mixed meal test … but not during an IVGTT [intravenous glucose tolerance test].

This is an interesting finding, because what damages our bodies is the blood sugar we experience after eating “a mixed meal” but so much research uses the artificial glucose tolerance (GTT) test to assess blood sugar health. This result suggests that the GTT may be missing important signs of early blood sugar dysfunction and that the mixed meal test may be a better diagnostic test than the GTT. I have long believed this to be true, since so many people experience reactive lows when they take the GTT which produces a seemingly “normal reading” though they routinely experience highs after eating meals. These highs are what damage our organs.

Here again we see evidence that long before obesity develops, people with this common diabetes gene variant show highly abnormal blood sugar behavior. Abnormal production of glucose by the liver may also contribute to obesity as metformin, a drug that that blocks the liver’s production of glucose blocks weight gain and often causes weight loss.

It has long been known that African-Americans have a much higher rate of diabetes and metabolic syndrome than the American population as a whole. This has been blamed on lifestyle, but a 2009 genetic study finds strong evidence that the problem is genetic.

The study reports,

Using genetic samples obtained from a cohort of subjects undergoing cardiac-related evaluation, a strict algorithm that filtered for genomic features at multiple levels identified 151 differentially-expressed genes between Americans of African ancestry and those of European ancestry. Many of the genes identified were associated with glucose and simple sugar metabolism, suggestive of a model whereby selective adaptation to the nutritional environment differs between populations of humans separated geographically over time.

In the full text discussion the authors state,

These results suggest that differences in glucose metabolism between Americans of African and European may reside at the transcriptional level. The down-regulation of these genes in the AA cohorts argues against these changes being a compensatory response to hyperglycemia and suggests instead a genetic adaptation to changes in the availability of dietary sugars that may no longer be appropriate to a Western Diet.

In conclusion the authors note that the vegetarian diet of the Seventh Day Adventists, often touted as proof of the usefulness of the “Diet Pyramid” doesn’t provide the touted health benefits to people of African American Heritage. Obviously, when hundreds of carbohydrate metabolizing genes aren’t working properly the diet needed is a low carbohydrate diet.

Gene that Disrupts Circadian Clock Associated with Type 2 Diabetes

It has been known for a while that people who suffer from sleep disturbances often suffer raised insulin resistance. In December of 2008, researchers identified a gene, “rs1387153, near MTNR1B (which encodes the melatonin receptor 2 (MT2)), as a modulator of fasting plasma glucose.” They conclude,

Melatonin levels appear to control the body clock which, in turn, regulates the secretion of substances that modify blood pressure, hormone levels, insulin secretion and many other processes throughout the body.

The Environmental Factors That Push Borderline Genes into Full-fledged Diabetes

We’ve seen so far that to get Type 2 Diabetes you seem to need to have some diabetes gene or genes, but that not everyone with these genes develops diabetes. There are what scientists call environmental factors that can push a borderline genetic case into full fledged diabetes. Let’s look now at what the research has found about what some of these environmental factors might be.

Your Mother’s Diet During Pregnancy May Have Caused Your Diabetes

Many “environmental factors” that scientists explore occur in the environment of the womb. Diabetes is no different, and the conditions you experienced when you were a fetus can have life-long impact on your blood sugar control.

Researchers following the children of mothers who had experienced a Dutch famine during World War II found that children of mothers who had experienced famine were far more likely to develop diabetes in later life than a control group from the same population whose mothers had been adequately fed.

A study of a Chinese population found a link between low birth weight and the development of both diabetes and impaired glucose regulation (i.e. prediabetes) that was independent of “sex, age, central obesity, smoking status, alcohol consumption, dyslipidemia, family history of diabetes, and occupational status.” Low birth weight in this population may well be due to less than optimal maternal nutrition during pregnancy.

This may not seem all that relevant to Americans whose mothers have not been exposed to famine conditions. But to conclude this is to forget how many American teens and young women suffer from eating disorders and how prevalent crash dieting is in the group of women most likely to get pregnant.

It is also true that until the 1980s obstetricians routinely warned pregnant women against gaining what is now understood to be a healthy amount of weight. When pregnant women started to gain weight, doctors often put them on highly restrictive diets which resulted in many case in the birth of underweight babies.

Your Mother’s Gestational Diabetes May Have Caused Your Diabetes

Maternal starvation is not the only pre-birth factor associated with an increased risk of diabetes. Having a well-fed mother who suffered gestational diabetes also increases a child’s risk both of obesity and of developing diabetes.

Pesticides and PCBs in Blood Stream Correlate with Incidence of Diabetes

A study conducted among members of New York State’s Mohawk tribe found that the odds of being diagnosed with diabetes in this population was almost 4 times higher in members who had high concentrations of PCBs in their blood serum. It was even higher for those with high concentrations of pesticides in their blood.

It is very important to note that there is no reason to believe this phenomenon is limited to people of Native American heritage. Upstate NY has a well-known and very serious PCB problem–remember Love Canal? And the entire population of the U.S. has been overexposed to powerful pesticides for a generation.

More evidence that obesity may be caused by exposure to toxic pollutants which damage genes comes in a study published January of 2009. This study tracked the exposure of a group of pregnant Belgian woman to several common pollutants: hexachlorobenzene, dichlorodiphenyldichloroethylene (DDE) , dioxin-like compounds, and polychlorinated biphenyls (PCBs). It found a correlation between exposure to PCBs and DDE and obesity by age 3, especially in children of mothers who smoked.

These studies, which garnered no press attention at all, probably have more to tell us about the reason for the so-called “diabetes epidemic” than any other published over the last decade.

BPA and Plasticizers from Packaging Are Strongly Linked to Obesity and Insulin Resistance

BPA, the plastic used to line most metal cans has long been suspected of causing obesity. Now we know why. A study published in 2008 reported that BPA suppresses a key hormone, adiponectin, which is responsible for regulating insulin sensitivity in the body and puts people at a substantially higher risk for metabolic syndrome.

You, and your children are getting far more BPA from canned foods than what health authorities assumed they were getting. A research report published in 2011 reported that the level of BPA actually measured in people’s bodies after they consumed canned soup turned out to be extremely high. People who ate a serving of canned soup every day for five days had BPA levels of 20.8 micrograms per liter of urine, whereas people who instead ate fresh soup had levels of 1.1 micrograms per liter.

Nevertheless, the FDA caved in to industry pressure in 2012 and refused to regulate BPA claiming that, as usual, more study was needed. (FDA: BPA)

BPA is not the only toxic chemical associated with plastics that may be promoting insulin resistance. . Phthalates are compounds added to plastic to make it flexible. They rub off on our food and are found in our blood and urine. A study of 387 Hispanic and Black, New York City children who were between six and eight years old measured the phthalates in their urine and found that the more phthalates in their urine, the fatter the child was a year later.

And phthalates are everywhere. A study of 1,016 Swedes aged 70 years and older found that four phthalate metabolites were detected in the blood serum of almost all the participants. High levels of three of these were associated with the prevalence of diabetes. The researchers explain that one metabolite was mainly related to poor insulin secretion, whereas two others were related to insulin resistance. The researchers didn’t check to see whether this relationship held for prediabetes.

Chances are very good that these same omnipresent phthalates are also causing insulin resistance and damaging insulin secretion in people whose ages fall between those of the two groups studied here.

Use of Herbicide Atrazine Maps to Obesity, Causes Insulin Resistance

A study published in April of 2009 mentions that “There is an apparent overlap between areas in the USA where the herbicide, atrazine (ATZ), is heavily used and obesity-prevalence maps of people with a BMI over 30.”

It found that when rats were given low doses of this pesticide in thier water, “Chronic administration of ATZ decreased basal metabolic rate, and increased body weight, intra-abdominal fat and insulin resistance without changing food intake or physical activity level.” In short the animals got fat even without changing their food intake. When the animals were fed a high fat,high carb diet, the weight gain was even greater.

Insulin resistance was increased too, which if it happens in people, means that people who have genetically-caused borderline capacity to secrete insulin are more likely to become diabetic when they are exposed to this chemical via food or their drinking water.

In 2007 scientists at New York’s Mount Sinai Hospital discovered that the intestine has receptors for sugar identical to those found on the tongue and that these receptors regulate secretion of glucagon-like peptide-1 (GLP-1). GLP-1 is the peptide that is mimicked by the diabetes drug Byetta and which is kept elevated by Januvia and Onglyza. You can read about that finding in this Science Daily report:

In November 2009, these same scientists reported that a very common herbicide 2,4 D blocked this taste receptor, effectively turning off its ability to stimulate the production GLP-1. The fibrate drugs used to lower cholesterol were also found to block the receptor.

What was even more of concern was the discovery that the ability of these compounds to block this gut receptor “did not generalize across species to the rodent form of the receptor.” The lead researcher was quoted as saying,

…most safety tests were done using animals, which have T1R3 receptors that are insensitive to these compounds,

This takes on additional meaning when you realize that most compounds released into the environment are tested only on animals, not humans. It may help explain why so many supposedly “safe” chemicals are damaging human glucose metabolisms.

Trace Amounts of Arsenic in Urine Correlate with Dramatic Rise in Diabetes

A study published in JAMA in August of 2008 found of 788 adults who had participated in the 2003-2004 National Health and Nutrition Examination Survey (NHANES) found those who had the most arsenic in their urine, were nearly four times more likely to have diabetes than those who had the least amount.

The New York Times report about this study (no longer online) added this illuminating bit of information to the story:

Arsenic can get into drinking water naturally when minerals dissolve. It is also an industrial pollutant from coal burning and copper smelting. Utilities use filtration systems to get it out of drinking water.

Seafood also contains nontoxic organic arsenic. The researchers adjusted their analysis for signs of seafood intake and found that people with Type 2 Diabetes had 26 percent higher inorganic arsenic levels than people without Type 2 Diabetes.

How arsenic could contribute to diabetes is unknown, but prior studies have found impaired insulin secretion in pancreas cells treated with an arsenic compound.

Another important environmental factor is this: Type 2 Diabetes can be caused by some commonly prescribed drugs. Beta blockers and atypical antipsychotics like Zyprexa have been shown to cause diabetes in people who would not otherwise get it. This is discussed here.

There is some research that suggests that SSRI antidepressants may also promote diabetes. It is well known that antidepressants cause weight gain.

Spin doctors in the employ of the drug companies who sell these high-profit antidepressants have long tried to attribute the relationship between depression and obesity to depression, rather than the drugs used to treat the condition.

However, a new study published in June 2009 used data from the Canadian National Population Health Survey (NPHS), a longitudinal study of a representative cohort of household residents in Canada and tracked the incidence of obesity over ten years.

The study found that, “MDE [Major Depressive Episode] does not appear to increase the risk of obesity. …Pharmacologic treatment with antidepressants may be associated with an increased risk of obesity. [emphasis mine]. The study concluded,

A study published in August 2009 analyzed data for 8599 survivors in the Childhood Cancer Survivor Study. It found that after adjusting for body mass and exercise levels, survivors of childhood cancer were 1.8 times more likely than the siblings to report that they had diabetes.

Even more significantly, those who had had full body radiation were 7.2 times more likely to have diabetes.

This raises the question of whether exposure to radiation in other contexts also causes Type 2 diabetes.

More Insight into the Effect of Genetic Flaws

Now that we have a better idea of some of the underlying physiological causes of diabetes, lets look more closely at the physiological processes that takes place as these genetic flaws push the body towards diabetes.

Insulin Resistance Develops in Thin Children of People with Type 2 Diabetes

Lab research has come up with some other intriguing findings that challenge the idea that obesity causes insulin resistance which causes diabetes. Instead, it looks like the opposite happens: Insulin resistance precedes the development of obesity.

One of these studies took two groups of thin subjects with normal blood sugar who were evenly matched for height and weight. The two groups differed only in that one group had close relatives who had developed Type 2 Diabetes, and hence, if there were a genetic component to the disorder, they were more likely to have it. The other group had no relatives with Type 2 Diabetes. The researchers then and examined the subjects’ glucose and insulin levels during a glucose tolerance test and calculated their insulin resistance. They found that the thin relatives of the people with Type 2 Diabetes already had much more insulin resistance than did the thin people with no relatives with diabetes.

This result was echoed by a second study published in November of 2009.

That study compared detailed measurements of insulin secretion and resistance in 187 offspring of people diagnosed with Type 2 diabetes against 509 controls. Subjects were matched with controls for age, gender and BMI. It concluded:

The first-degree offspring of type 2 diabetic patients show insulin resistance and beta cell dysfunction in response to oral glucose challenge. Beta cell impairment exists in insulin-sensitive offspring of patients with type 2 diabetes, suggesting beta cell dysfunction to be a major defect determining diabetes development in diabetic offspring.

Mitochondrial Dysfunction is Found in Lean Relatives of People with Type 2 Diabetes

One reason insulin resistance might precede obesity was explained by a landmark 2004 study which looked at the cells of the “healthy, young, lean” but insulin-resistant relatives of people with Type 2 Diabetes and found that their mitochondria, the “power plant of the cells” that is the part of the cell that burns glucose, appeared to have a defect. While the mitochondria of people with no relatives with diabetes burned glucose well, the mitochondria of the people with an inherited genetic predisposition to diabetes were not able to burn off glucose as efficiently, but instead caused the glucose they could not burn and to be stored in the cells as fat.

More Evidence that Abnormal Insulin Resistance Precedes Weight Gain and Probably Causes It

A study done by the same researchers at Yale University School of Medicine who discovered the mitochondrial problem we just discussed was published in Proceedings of the National Academy of Science (PNAS) in July 2007. It reports on a study that compared energy usage by lean people who were insulin resistant and lean people who were insulin sensitive.

Using new imaging technologies, the researchers found that lean but insulin resistant subjects converted glucose from high carbohydrate meals into triglycerides–i.e. fat. Lean insulin-sensitive subjects, in contrast, stored the same glucose in the form of muscle and liver glycogen.

The researchers conclude that:

the insulin resistance, in these young, lean, insulin resistant individuals, was independent of abdominal obesity and circulating plasma adipocytokines, suggesting that these abnormalities develop later in the development of the metabolic syndrome.”

In short, obesity looked to be a result, not a cause of the metabolic flaw that led these people to store carbohydrate they ate in the form of fat rather than burn it for energy.

The researchers suggested controlling insulin resistance with exercise. It would also be a good idea for people who are insulin resistant, or have a family history of Type 2 Diabetes to cut back on their carb intake, knowing that the glucose from the carbs they eat is more likely to turn into fat.

Beta Cells Fail to Reproduce in People with Diabetes

A study of pancreas autopsies that compared the pancreases of thin and fat people with diabetes with those of thin and fat normal people found that fat, insulin-resistant people who did not develop diabetes apparently were able to grow new beta-cells to produce the extra insulin they needed. In contrast, the beta cells of people who developed diabetes were unable to reproduce. This failure was independent of their weight.

The research team identified a “fat-burning” gene, the products of which are required to maintain the cells insulin sensitivity. They also discovered that this gene is reduced in muscle tissue from people with high blood sugar and type 2-diabetes. In the absence of the enzyme that is made by this gene, muscles have reduced insulin sensitivity, impaired fat burning ability, which leads to an increased risk of developing obesity.

“The expression of this gene is reduced when blood sugar rises, but activity can be restored if blood sugar is controlled by pharmacological treatment or exercise”, says Professor Juleen Zierath. “Our results underscore the importance of tight regulation of blood sugar for people with diabetes.”

In short, once your blood sugar rises past a certain point, you become much more insulin resistant. This, in turn, pushes up your blood sugar more.

A New Model For How Diabetes Develops

These research findings open up a new way of understanding the relationship between obesity and diabetes.

Perhaps people with the genetic condition underlying Type 2 Diabetes inherit a defect in the beta cells that make those cells unable to reproduce normally to replace cells damaged by the normal wear and tear of life.Or perhaps exposure to an environmental toxin damages the related genes.

Perhaps, too, a defect in the way that their cells burn glucose inclines them to turn excess blood sugar into fat rather than burning it off as a person with normal mitochondria might do.

Put these facts together and you suddenly get a fatal combination that is almost guaranteed to make a person fat.

Studies have shown that blood sugars only slightly over 100 mg/dl are high enough to render beta cells dysfunctional.

In a normal person who had the ability to grow new beta cells, any damaged beta cells would be replaced by new ones, which would keep the blood sugar at levels low enough to avoid further damage. But the beta cells of a person with a genetic heritage of diabetes are unable to reproduce So once blood sugars started to rise, more beta cells would succumb to the resulting glucose toxicity, and that would, in turn raise blood sugar higher.

As the concentration of glucose in their blood rose, these people would not be able to do what a normal person does with excess blood sugar–which is to burn it for energy. Instead their defective mitochondria will cause the excess glucose to be stored as fat. As this fat gets stored in the muscles it causes the insulin resistance so often observed in people with diabetes–long before the individual begins to gain visible weight. This insulin resistance puts a further strain on the remaining beta cells by making the person’s cells less sensitive to insulin. Since the person with an inherited tendency to diabetes’ pancreas can’t grow the extra beta cells that a normal person could grow when their cells become insulin resistant this leads to ever escalating blood sugars which further damage the insulin-producing cells, and end up in the inevitable decline into diabetes.

Low Fat Diets Promote the Deterioration that Leads to Diabetes in People with the Genetic Predisposition

In the past two decades, when people who were headed towards diabetes begin to gain weight, they were advised to eat a low fat diet. Unfortunately, this low fat diet is also a high carbohydrate diet–one that exacerbates blood sugar problems by raising blood sugars dangerously high, destroying more insulin-producing beta-cells, and catalyzing the storage of more fat in the muscles of people with dysfunctional mitochondria. Though they may have stuck to diets to low fat for weeks or even months these people were tormented by relentless hunger and when they finally went off their ineffective diets, they got fatter. Unfortunately, when they reported these experiences to their doctors, they were almost universally accused of lying about their eating habits.

It has only been documented in medical research during the past two years that that many patients who have found it impossible to lose weight on the low fat high carbohydrate can lose weight–often dramatically–on a low carbohydrate diet while improving rather than harming their blood lipids.

The low carb diet does two things. By limiting carbohydrate, it limits the concentration of blood glucose which often is enough to bring moderately elevated blood sugars down to normal or near normal levels. This means that there will be little excess glucose left to be converted to fat and stored.

It also gets around the mitochondrial defect in processing glucose by keeping blood sugars low so that the body switches into a mode where it burns ketones rather than glucose for muscle fuel.

Relentless Hunger Results from Roller Coaster Blood Sugars

There is one last reason why you may believe that obesity caused your diabetes, when, in fact, it was undiagnosed diabetes that caused your obesity.

Long before a person develops diabetes, they go through a phase where they have what doctors called “impaired glucose tolerance.” This means that after they eat a meal containing carbohydrates, their blood sugar rockets up and may stay high for an hour or two before dropping back to a normal level.

What most people don’t know is that when blood sugar moves swiftly up or down most people will experience intense hunger. The reasons for this are not completely clear. But what is certain is that this intense hunger caused by blood sugar swings can develop years before a person’s blood sugar reaches the level where they’ll be diagnosed as diabetic.

This relentless hunger, in fact, is often the very first diabetic symptom a person will experience, though most doctors do not recognize this hunger as a symptom. Instead, if you complain of experiencing intense hunger doctors may suggest you need an antidepressant or blame your weight gain, if you are female, on menopausal changes.

This relentless hunger caused by impaired glucose tolerance almost always leads to significant weight gain and an increase in insulin resistance. However, because it can take ten years between the time your blood sugar begins to rise steeply after meals and the time when your fasting blood sugar is abnormal enough for you to be diagnosed with diabetes, most people are, indeed, very fat at the time of diagnosis.

With better diagnosis of diabetes (discussed here) we would be able to catch early diabetes before people gained the enormous amounts of weight now believed to cause the syndrome. But at least now people with diabetic relatives who are at risk for developing diabetes can go a long way towards preventing the development of obesity by controlling their carbohydrate intake long before they begin to put on weight.

You CAN Undo the Damage

No matter what your genetic heritage or the environmental insults your genes have survived, you can take steps right now to lower your blood sugar, eliminate the secondary insulin resistance caused by high blood sugars, and start the process that leads back to health. The pages linked here will show you how.

In Dante Alighieri’s Divine Comedy the narrator meets a man named Ciacco who had been sent to Hell for the “Damning sin of Gluttony.” According to Catholic theology, in order to end up in Hell one must willfully commit a serious sin. So Dante believed that fat people chose to be fat. This antiquated view of the cause of obesity is still widespread, even among medical professionals. The consequences of this misconception are significant, because it forms the basis for the discrimination suffered by the obese; for the wasting of scarce resources in attempts to change lifestyle habits by public education; and for the limited availability of subsidized obesity treatments.

While obesity is often labeled a lifestyle disease, poor lifestyle choices alone account for only a 6 to 8 kg weight gain. The body has a powerful negative feedback system to prevent excessive weight gain. The strongest inhibitor of hunger, the hormone leptin, is made by fat cells. A period of increased energy intake will result in fat deposition, which will increase leptin production. Leptin suppresses hunger and increases energy expenditure. This slows down weight gain. To become obese, it may be necessary to harbor a genetic difference that makes the individual resistant to the action of leptin.

Evidence from twin and adoption studies suggests that obesity has a genetic basis, and over the past two decades a number of genes associated with obesity have been described. The most common genetic defect in European populations leading to severe obesity is due to mutations in the gene coding for the melanocortin 4 receptor (MCR4). Still, this defect can explain severe obesity in only approximately 6 percent to 7 percent of cases (J Clin Invest, 106:271-79, 2000). Other genes have been discovered that can cause milder increases in weight; for example, variants of just one gene (FTO) can explain up to 3 kg of weight variation between individuals (Science, 316:889-94, 2007).

Genes do not directly cause weight gain. Rather, genes influence the desire for food and the feeling of satiety. In an environment with either poor access to food or access to only low-calorie food, obesity may not develop even in persons with a genetic predisposition. When there is an abundance of food and a sedentary lifestyle, however, an obesity-prone person will experience greater hunger and reduced satiety, increasing caloric intake and weight gain.

Since the 1980s, there has been a rapid rise in the prevalence of obesity worldwide, a trend that likely results from a variety of complex causes. There is increasing evidence, for example, that the development of obesity on individual or familial levels may be influenced by environmental experiences that occur in early life. For example, if a mother is malnourished during early pregnancy, this results in epigenetic changes to genes involved in the set points for hunger and satiety in the developing child. These changes may then become fixed, resulting in a tendency towards obesity in the offspring.

The biological basis of obesity is further highlighted by the vigorous defense of weight following weight loss. There are at least 10 circulating hormones that modulate hunger. Of these, only one has been confirmed as a hunger-inducing hormone (ghrelin), and it is made and released by the stomach. In contrast, nine hormones suppress hunger, including CCK, PYY, GLP-1, oxyntomodulin, and uroguanylin from the small bowel; leptin from fat cells; and insulin, amylin, and pancreatic polypeptide from the pancreas.

After weight loss, regardless of the diet employed, there are changes in circulating hormones involved in the regulation of body weight. Ghrelin levels tend to increase and levels of multiple appetite-suppressing hormones decrease. There is also a subjective increase in appetite. Researchers have shown that even after three years, these hormonal changes persist (NEJM, 365:1597-604, 2011; Lancet Diabetes and Endocrinology, 2:954-62, 2014). This explains why there is a high rate of weight regain after diet-induced weight loss.

Given that the physiological responses to weight loss predispose people to regain that weight, obesity must be considered a chronic disease. Data show that those who successfully maintain their weight after weight loss do so by remaining vigilant and constantly applying techniques to oppose weight regain. These techniques may involve strict diet and exercise practices and/or pharmacotherapy.

It is imperative for society to move away from a view that obesity is simply a lifestyle issue and to accept that it is a chronic disease. Such a change would not only relieve the stigma of obesity but would also empower politicians, scientists and clinicians to tackle the problem more effectively.

Joseph Proietto was the inaugural Sir Edward Dunlop Medical Research Foundation Professor of Medicine in the Department of Medicine, Austin Health at the University of Melbourne in Australia. He is a researcher and clinician investigating and treating obesity and type 2 diabetes.

THE ENDOCRINE THEORY: Some researchers have posited that fat cells may secrete molecules that affect glucose homeostasis in muscle or liver tissue.COURTESY OF MITCHELL LAZAR

In the early 19th century, Belgian mathematician Adolphe Quetelet was obsessed with a shape: the bell curve. While helping with a population census, Quetelet proposed that the spread of human traits such as height and weight followed this trend, also known as a Gaussian or normal distribution. On a quest to define a “normal man,” he showed that human height and weight data fell along his beloved bell curves, and in 1823 devised the “Quetelet Index”—more familiar to us today as the BMI, or body mass index, a ratio of weight to height.

Nearly two centuries later, clinicians, researchers, and fitness instructors continue to rely on this metric to pigeonhole people into categories: underweight, healthy, overweight, or obese. But Quetelet never intended the metric to serve as a way to define obesity. And now, a growing body of evidence suggests these categories fail to accurately reflect the health risks—or benefits—of being overweight.

Although there is considerable debate surrounding the prevalence of metabolically healthy obesity, when obesity is defined in terms of BMI (a BMI of 30 or higher), estimates suggest that about 10 percent of adults in the U.S. are obese yet metabolically healthy, while as many as 80 percent of those with a normal BMI may be metabolically unhealthy, with signs of insulin resistance and poor circulating lipid levels, even if they suffer no obvious ill effects. “If all we know about a person is that they have a certain body weight at a certain height, that’s not enough information to know their health risks from obesity,” says health-science researcher Paul McAuley of Winston-Salem State University. “We need better indicators of metabolic health.”

The dangers of being overweight, such as a higher risk of heart disease, type 2 diabetes, and other complications, are well known. But some obese individuals—dubbed the “fat fit”—appear to fare better on many measures of health when they’re heavier. Studies have found lower mortality rates, better response to hemodialysis in chronic kidney disease, and lower incidence of dementia in such people. Mortality, it’s been found, correlates with obesity in a U-shaped curve (J Sports Sci, 29:773-82, 2011). So does extra heft help or hurt?

To answer that question, researchers are trying to elucidate the metabolic reasons for this obesity paradox.

In a recent study, Harvard University epidemiologist Goodarz Danaei and his colleagues analyzed data from nine studies involving a total of more than 58,000 participants to tease apart how obesity and other well-known metabolic risk factors influence the risk of coronary heart disease. Controlling these other risk factors, such as hypertension or high cholesterol, with medication is simpler than curbing obesity itself, Danaei explains. “If you control a person’s obesity you get rid of some health risks, but if you control hypertension or diabetes, that also reduces health risks, and you can do the latter much more easily right now.”

Danaei’s team assessed BMI and metabolic markers such as systolic blood pressure, total serum cholesterol, and fasting blood glucose. The three metabolic markers only explained half of the increased risk of heart disease across all study participants. In obese individuals, the other half appeared to be mediated by fat itself, perhaps via inflammatory markers or other indirect mechanisms (Epidemiology, 26:153-62, 2015). While Danaei’s study was aimed at understanding how obesity hurts health, the results also uncovered unknown mechanisms by which excess adipose tissue might exert its effects. This particular study revealed obesity’s negative effects, but might these unknown mechanisms hold clues that explain the obesity paradox?

Other researchers have suggested additional possibilities—for example, that inflammatory markers such as TNF-α help combat conditions such as chronic kidney disease, or that obesity makes a body more capable of making changes to, and tolerating changes in, blood flow depending on systemic needs (Am J Clin Nutr, 81:543-54, 2005).

According to endocrinologist Mitchell Lazar at the University of Pennsylvania, the key to explaining the obesity paradox may be two nonexclusive ways fat tissue is hypothesized to function. One mechanism, termed the endocrine theory, suggests that fat cells secrete, or don’t secrete enough of, certain molecules that influence glucose homeostasis in other tissues, such as muscle or liver. The first such hormone to be discovered was leptin; later studies reported several other adipocyte-secreted factors, including adiponectin, resistin, and various cytokines.

The other hypothesis, dubbed the spillover theory, suggests that storing lipids in fat cells has some pluses. Adipose tissue might sequester fat-soluble endotoxins, and produce lipoproteins that can bind to and clear harmful lipids from circulation. When fat cells fill up, however, these endotoxins are stashed in the liver, pancreas, or other organs—and that’s when trouble begins. In “fat fit” people, problems typically linked to obesity such as high cholesterol or diabetes may be avoided simply because their adipocytes mop up more endotoxins.

“In this model, one could imagine that if you could store even more fat in fat cells, you could be even more obese, but you might be protected from problems [associated with] obesity because you’re protecting the other tissues from filling up with lipids that cause problems,” says Lazar. “This may be the most popular current model to explain the fat fit.”

Although obesity greatly increases the risk of type 2 diabetes—up to 93-fold in postmenopausal women, for example—not all obese people suffer from the condition. Similarly, a certain subtype of individuals with “normal” BMIs are at greater risk of developing insulin resistance and type 2 diabetes than others with BMIs in the same range. Precisely what distinguishes these two cohorts is still unclear. “Just as important as explaining why some obese people don’t get diabetes is to explain why other subgroups—normal-weight people or those with lipodystrophy—sometimes get it,” Lazar says. “If there are multiple subtypes of obesity and diabetes, can we figure out genetic aspects or biomarkers that cause one of these phenotypes and not the other?”

To Lazar, McAuley, and other researchers, it’s increasingly evident that BMI may not be that metric. Finding better ways to assess a healthy weight, however, has proven challenging. Researchers have tested measures, such as the body shape index (ABSI) or the waist-hip ratio, which attempt to gauge visceral fat—considered to be more metabolically harmful than fat in other body locations. However, these metrics have yet to be implemented widely in clinics, and few are as simple to understand as the BMI (Science, 341:856-58, 2013).

Independent of metrics, however, the health message regarding weight is still unanimous: exercise and healthy dietary choices benefit everyone. “At a certain point, despite all the so-called fit-fat people, the demographics say that there’s a huge risk of diabetes and heart disease at very high BMI,” notes Lazar. “We can’t assume we’ll be one of the lucky ones who will have a BMI in the obese category but will still be protected from heart disease.”

Correction (November 2): The original version of this article misattributed the pull quote above. The attribution for this quote has been corrected, and The Scientist regrets the error.

In this review, we examine the original obesity paradox phenomenon (i.e. in cardiovascular disease populations, obese patients survive better), as well as three other related paradoxes (pre-obesity, “fat but fit” theory, and “healthy” obesity). An obesity paradox has been reported in a range of cardiovascular and non-cardiovascular conditions. Pre-obesity (defined as a body mass index of 25.0-29.9 kg · m⁻²) presents another paradox. Whereas “overweight” implies increased risk, it is in fact associated with decreased mortality risk compared with normal weight. Another paradox concerns the observation than when fitness is taken into account, the mortality risk associated with obesity is offset. The final paradox under consideration is the presence of a sizeable subset of obese individuals who are otherwise healthy. Consequently, a large segment of the overweight and obese population is not at increased risk for premature death. It appears therefore that low cardiorespiratory fitness and inactivity are a greater health threat than obesity, suggesting that more emphasis should be placed on increasing leisure time physical activity and cardiorespiratory fitness as the main strategy for reducing mortality risk in the broad population of overweight and obese adults.

The ability of insulin to stimulate glucose disposal varies more than six-fold in apparently healthy individuals. The one third of the population that is most insulin resistant is at greatly increased risk to develop cardiovascular disease (CVD), type 2 diabetes, hypertension, stroke, nonalcoholic fatty liver disease, polycystic ovary disease, and certain forms of cancer. Between 25-35% of the variability in insulin action is related to being overweight. The importance of the adverse effects of excess adiposity is apparent in light of the evidence that more than half of the adult population in the United States is classified as being overweight/obese, as defined by a body mass index greater than 25.0 kg/m(2). The current epidemic of overweight/obesity is most-likely related to a combination of increased caloric intake and decreased energy expenditure. In either instance, the fact that CVD risk is increased as individuals gain weight emphasizes the gravity of the health care dilemma posed by the explosive increase in the prevalence of overweight/obesity in the population at large. Given the enormity of the problem, it is necessary to differentiate between the CVD risk related to obesity per se, as distinct from the fact that the prevalence of insulin resistance and compensatory hyperinsulinemia are increased in overweight/obese individuals. Although the majority of individuals in the general population that can be considered insulin resistant are also overweight/obese, not all overweight/obese persons are insulin resistant. Furthermore, the cluster of abnormalities associated with insulin resistance – namely, glucose intolerance, hyperinsulinemia, dyslipidemia, and elevated plasma C-reactive protein concentrations — is limited to the subset of overweight/obese individuals that are also insulin resistant. Of greater clinical relevance is the fact that significant improvement in these metabolic abnormalities following weight loss is seen only in the subset of overweight/obese individuals that are also insulin resistant. In view of the large number of overweight/obese subjects at potential risk to be insulin resistant/hyperinsulinemic (and at increased CVD risk), and the difficulty in achieving weight loss, it seems essential to identify those overweight/obese individuals who are also insulin resistant and will benefit the most from weight loss, then target this population for the most-intensive efforts to bring about weight loss.

After weight loss, changes in the circulating levels of several peripheral hormones involved in the homeostatic regulation of body weight occur. Whether these changes are transient or persist over time may be important for an understanding of the reasons behind the high rate of weight regain after diet-induced weight loss.

Weight loss (mean [±SE], 13.5±0.5 kg) led to significant reductions in levels of leptin, peptide YY, cholecystokinin, insulin (P<0.001 for all comparisons), and amylin (P=0.002) and to increases in levels of ghrelin (P<0.001), gastric inhibitory polypeptide (P=0.004), and pancreatic polypeptide (P=0.008). There was also a significant increase in subjective appetite (P<0.001). One year after the initial weight loss, there were still significant differences from baseline in the mean levels of leptin (P<0.001), peptide YY (P<0.001), cholecystokinin (P=0.04), insulin (P=0.01), ghrelin (P<0.001), gastric inhibitory polypeptide (P<0.001), and pancreatic polypeptide (P=0.002), as well as hunger (P<0.001).

One year after initial weight reduction, levels of the circulating mediators of appetite that encourage weight regain after diet-induced weight loss do not revert to the levels recorded before weight loss. Long-term strategies to counteract this change may be needed to prevent obesity relapse. (Funded by the National Health and Medical Research Council and others; ClinicalTrials.gov number,NCT00870259.)

Large genome wide association studies have demonstrated that variants in the FTO gene have the strongest association with obesity risk in the general population, but the mechanism of the association has been unclear. However, a nonocoding causal variant in FTO has now been identified that changes the function of adipocytes from energy utilization (beige fat) to energy storage (white fat) with a fivefold decrease in mitochondrial thermogenesis [17]. When the effect of the variant was blocked in genetically engineered mice, thermogenesis increased and weight gain did not occur, despite eating a high-fat diet. Blocking the gene’s effect in human adipocytes also increased energy utilization. This observation has important implications for potential new anti-obesity drugs. (See “Pathogenesis of obesity”, section on ‘FTO variants’.)

Liraglutide for the treatment of obesity (July 2015)

Along with diet, exercise, and behavior modification, drug therapy may be a helpful component of treatment for select patients who are overweight or obese. Liraglutide is a glucagon-like peptide-1 (GLP-1) receptor agonist, used for the treatment of type 2 diabetes, and can promote weight loss in patients with diabetes, as well as those without diabetes.

●In a randomized trial in nondiabetic patients who had a body mass index (BMI) of ≥30 kg/m2 or ≥27 kg/m2 with dyslipidemia and/or hypertension, liraglutide 3 mg once daily, compared with placebo, resulted in greater mean weight loss (-8.0 versus -2.6 kg with placebo) [18]. In addition, cardiometabolic risk factors, glycated hemoglobin (A1C), and quality of life improved modestly. Gastrointestinal side effects transiently affected at least 40 percent of the liraglutide group and were the most common reason for withdrawal (6.4 percent). Liraglutide is an option for select overweight or obese patients, although gastrointestinal side effects (nausea, vomiting) and the need for a daily injection may limit the use of this drug. (See “Obesity in adults: Drug therapy”, section on ‘Liraglutide’.)

●In a trial designed specifically to evaluate the effect of liraglutide on weight loss in overweight or obese patients with type 2 diabetes (mean weight 106 kg), liraglutide, compared with placebo, resulted in greater mean weight loss (-6.4 kg and -5.0 kg for liraglutide 3 mg and 1.8 mg, respectively, versus -2.2 kg for placebo) [19]. Treatment with liraglutide was associated with better glycemic control, a reduction in the use of oral hypoglycemic agents, and a reduction in systolic blood pressure. Although liraglutide is not considered as initial therapy for the majority of patients with type 2 diabetes, it is an option for select overweight or obese patients with type 2 diabetes who fail initial therapy with lifestyle intervention and metformin. (See “Glucagon-like peptide-1 receptor agonists for the treatment of type 2 diabetes mellitus”, section on ‘Weight loss’.)

The Skinny on Fat Cells

Bruce Spiegelman has spent his career at the forefront of adipocyte differentiation and metabolism.

It’s hard to know whether you have the right stuff to be a scientist, but I had a passion for the research,” says Bruce Spiegelman, professor of cell biology at Harvard Medical School and the Dana-Farber Cancer Institute. After receiving his PhD in biochemistry from Princeton University in 1978, Spiegelman sent an application to do postdoctoral research to just one lab. “I wasn’t thinking I should apply to five different labs. I just marched forward more or less in a straight line,” he says. Spiegelman did know that he had no financial backup and depended on research fellowships throughout the early phase of his science career. “I thought it was fantastic, and still think so, that a PhD in science is supported by the government. I certainly appreciated that, because many of my friends in the humanities had to support themselves by cobbling together fellowships and teaching every semester, whereas we didn’t face similar challenges in the sciences.”

Since his graduate student days, Spiegelman has realized his potential, pioneering the study of adipose tissue biology and metabolism. He was introduced to the field in Howard Green’s laboratory, then at MIT, where Spiegelman began his one and only postdoc in 1978. Green had recently developed a system for culturing adipose cells and asked Spiegelman if he wanted to study fat cell differentiation. “I knew nothing about adipose tissue, but I was really interested in any model of how one cell switches to another. Whether skin or fat didn’t matter too much to me, because I was not coming at this from the perspective of physiology but from the perspective of how do these switches work at a molecular level?”

Spiegelman has stuck with studying the biology and differentiation of fat cells for more than 30 years. While looking for the master transcriptional regulator of fat development—which his laboratory found in 1994—Spiegelman’s group also discovered one of the first examples of a nuclear oncogene that functions as a transcription factor, and, more recently, the team found that brown fat and white fat come from completely different origins and that brown and beige fat are distinct cell types. Spiegelman was also the first to provide evidence for the connection between inflammation, insulin resistance, and fat tissue.

Here, Spiegelman talks about his strong affinity for the East Coast, his laboratory’s search for molecules that can crank up brown fat production and activity, and the culture of his laboratory’s weekly meeting.

Spiegelman Sets Out

First publication. Spiegelman grew up in Massapequa, New York, a town on Long Island. “Birds, insects, fish, and animals were fascinating to me. As a kid, I imagined I would be a wildlife ranger,” he says. Spiegelman and his brother were the first in their family to attend college; Spiegelman entered the College of William and Mary in 1970 thinking he would major in psychology. But before taking his first psychology course, he had to take a biology course, really loved it, and switched his major. For his senior thesis, he chose one of the few labs that did biochemistry-related research. He studied cultures of the filamentous fungus Aspergillus ornatus in which he induced the upregulation of a metabolic enzyme. Spiegelman applied a calculus transformation that related the age of the culture to the age of individual cells, something that had not been previously done. The work earned him his first first-author publication in 1975. “It was not a great breakthrough, but I think it showed that I was maybe applying myself more than the typical undergraduate.”

Full steam ahead. “My interest in laboratory research was intense. Even though it was not particularly inspired work, the first-author publication in a college where not many of the professors published a lot gave me a lot of confidence. It was probably out of proportion to the quality of the actual work.” That confidence and Spiegelman’s interest in the chemistry of living things led him to pursue a PhD in biochemistry at Princeton University. “Very early on, I felt that I couldn’t understand biology if it didn’t go to the molecular level. To me, just describing how an animal lived without understanding how it worked was very unsatisfying. I think it was one of the best decisions that I made in my life, to do a PhD in biochemistry,” he says, “because if you really want to understand living systems, you are very limited in how you can understand them without having a strong background in biochemistry because these are, essentially, chemical systems.”

Embracing molecular biology. Spiegelman initially joined Arthur Pardee’s laboratory, but switched when Pardee left Princeton for Harvard University in 1975. Because he was already collaborating with Marc Kirschner, a cell biologist and biochemist who studies the regulation of the cell cycle and how the cytoskeleton works, it was an easy transition to transfer to the new laboratory. In Kirschner’s group, Spiegelman became the cell biologist among many protein biochemists working on microtubule assembly in vitro. Rather than understanding how the proteins fit together to form the filamentous structures, Spiegelman wanted to understand what controlled their assembly inside cells. Working in mammalian cells, Spiegelman published three consecutive Cell papers on how microtubule assembly occurs in vivo. The firstpaper, from 1977, demonstrated that a nucleotide functions to stabilize the tubulin molecule rather than to regulate tubulin assembly in vivo.

Spiegelman Simmers

A new tool. For his next move, Spiegelman wanted to marry his background in biochemistry and molecular biology with a good cellular model system. He became interested in differentiation at the end of his PhD, while studying how the cytoskeleton is reorganized during neural differentiation, and settled on Green’s MIT laboratory for his postdoc. Green had developed a way to study both skin and fat cell differentiation. Again, Spiegelman was the odd man out, working on the molecular biology of fat cell differentiation while most of the graduate students and postdocs focused on the cellular biology of skin cell differentiation. While there, Spiegelman learned how to clone cDNA—a new method that some researchers thought was just another new fad, he says. “I thought it was pretty obvious that this was a tool that would be a game changer. I could see how I could clone some of the cDNAs and genes that were regulated in the fat cell lineage and then try to understand the regulation of these genes.”

Setting the stage. Spiegelman demonstrated that cAMP regulates the synthesis of certain enzymes in fat cells during differentiation. But while this was the most influential paper from his postdoc, says Spiegelman, it was his demonstration of cloning mRNAs from adipocytes, published in 1983, that set the stage for cloning fat-selective genes. The work, mostly done when Spiegelman was already a new faculty member at the Dana-Farber Cancer Institute, stemmed from his learning molecular cloning in Phillip Sharp’s lab at MIT and Bryan Roberts’s lab at Harvard. “This was the raw material from which we eventually cloned PPARγ and showed it to be the master regulator of fat [cell] development.”

Roots. Spiegelman became an assistant professor at the Harvard Medical School in 1982, when he was not yet 30. Although he had entertained the idea of moving to the West Coast with his wife, whom he had met at Princeton where she obtained a PhD in French literature, Spiegelman says he is really an East Coaster at heart. “My wife and I came to love Boston and were very comfortable there. Our families were both in New York, which was close, but not too close, and we really enjoyed the culture and pace of Boston; it was more ‘us.’ We really liked to visit California but didn’t particularly want to move there. We’re both real Northeastern people.”

Relating to Sisyphus. The transition from doing a postdoc to setting up his own laboratory was “very exciting and terribly stressful,” says Spiegelman. “When I think back, I always tried to be professional with my laboratory, but I was so stressed at suddenly being on my own with no management training.” The people resources he had encountered in his graduate and postdoctoral training labs were also not there yet, and he says his first publication as a principal investigator was like pushing a rock up a hill. But eventually, Spiegelman’s lab built a reputation and reached a critical mass of talented people who advanced the science. Again in 1983, Spiegelman produced a publication showing that morphological manipulation can affect gene expression and adipose differentiation.

A paler shade of brown. More recently, in 2012, Spiegelman’s laboratory showed that within adult white adipose tissue, there are pockets of a yet another type of fat tissue that he called beige fat. “I think the evidence is very good from rodents that if you activate brown and beige fat, you get metabolic benefit both in obesity and diabetes. So the question now is: Can that be done in humans in a way that’s beneficial and not toxic?” The lab is now looking to identify molecules that can either ramp up the activity of brown and beige fat or increase the production of both cell types as possible therapeutics for metabolic disorders or even cancer-associated cachexia. “Anyone who says that either approach will work better is being foolish. We just don’t know enough to go after just one or the other.”

On the irisin controversy. After reporting in 2012 that a muscle-related hormone called irisin could switch white fat to metabolically active brown fat, Spiegelman became embroiled in a media-covered debate about whether the molecule really exists; he was also the victim of a potential fraud plot. Most recently, Spiegelman provided thorough evidence that irisin does in fact exist. On the controversy, he says it’s a fine line between defending his scientific integrity and not adding more fuel to the fire or engaging with his harassers. “We have a long track record of doing credible and reproducible science and it was not that complicated to address the paper that claimed irisin was ‘a myth.’ That study used very outmoded scientific approaches.”

Raw talent. Many of Spiegelman’s trainees have gone on to become very successful scientists, including Tontonoz, Hotamisligil, Evan Rosen, and Randy Johnson. “It’s a quantum change in the experience of doing science when you get people who have their own visions. I would have thought that interacting with smart people would mainly help me get my scientific vision accomplished. And that was partly true, but also it changed my vision. When you have people challenging you on a day-to-day basis, you learn from them through the questions they ask and the way they challenge you in a constructive way. They made me a much better scientist.”

Rigorous mentorship. “I feel very passionately that a major part of my job is to prepare the next generation of scientists. Everyone who comes through my lab will tell you that I take that very seriously. We make sure my students give a lot of talks and get critical assessments of their presentations to our lab group. I am very hands-on both scientifically and in developing the way students project their vision. I had a very good mentor, Marc Kirschner, and I’d like to think that I learned how to be a mentor from him. I want to make sure that when people walk out of my lab they are prepared to run independent research programs.”

Greatest Hits

Identified the master regulator of adipogenesis, the nuclear receptor PPARγ

Was the first to show that a nuclear oncogene, c-fos, codes for a transcription factor that binds to the promoters of genes

•A high-fat diet augments Th17 cell development and the expression of Acaca

•ACC1 controls Th17 cell development in vitro and Th17 cell pathogenicity in vivo

•ACC1 modulates RORγt function in developing Th17 cells

•Obesity in humans induces ACACA and IL-17A expression in CD4 T cells

Chronic inflammation due to obesity contributes to the development of metabolic diseases, autoimmune diseases, and cancer. Reciprocal interactions between metabolic systems and immune cells have pivotal roles in the pathogenesis of obesity-associated diseases, although the mechanisms regulating obesity-associated inflammatory diseases are still unclear. In the present study, we performed transcriptional profiling of memory phenotype CD4 T cells in high-fat-fed mice and identified acetyl-CoA carboxylase 1 (ACC1, the gene product of Acaca) as an essential regulator of Th17 cell differentiation in vitro and of the pathogenicity of Th17 cells in vivo. ACC1 modulates the DNA binding of RORγt to target genes in differentiating Th17 cells. In addition, we found a strong correlation between IL-17A-producing CD45RO(+)CD4 T cells and the expression of ACACA in obese subjects. Thus, ACC1 confers the appropriate function of RORγt through fatty acid synthesis and regulates the obesity-related pathology of Th17 cells.

Obesity often comes with a side of chronic inflammation, causing inflammatory chemicals and immune cells to flood adipose tissue, the hypothalamus, the liver, and other areas of the body. Inflammation is a big part of what makes obesity such an unhealthy condition, contributing to Type 2 diabetes, heart disease, cancers, autoimmune disorders, and possibly even neurodegenerative diseases.

To better understand the relationship between obesity and inflammation, Toshinori Nakayama, Yusuke Endo, and their colleagues at Chiba University in Japan started with what often leads to obesity: a high-fat diet. They fed mice rich meals for a couple of months and looked at how gene expression in the animals’ T cells compared to gene expression in the T cells of mice fed a normal diet. Most notably, they found increased expression ofAcaca, a gene that codes for a fatty acid synthesis enzyme called acetyl coA carboxylase 1 (ACC1). They went on to show that the resulting increase in fatty acid levels pushed CD4 T cells to differentiate into inflammatory T helper 17 (Th17) cells.

Th17 cells help fight off invading fungi and some bacteria. But these immune cells can also spin out of control in autoimmune diseases such as multiple sclerosis. Nakayama’s team showed that either blocking ACC1 activity with a drug called TOFA or deleting a key portion of Acaca in mouse CD4 T cells reduced the generation of pathologic Th17 cells. Overexpressing Acaca increased Th17-cell generation.

The researchers also demonstrated that mice fed a high-fat diet had elevated susceptibility to a multiple sclerosis–like disease, and that TOFA reduced the symptoms.

“This is a very intriguing finding, suggesting not only that obesity can directly induce Th17 differentiation but also indicating that pharmacologic targeting of fatty acid synthesis may help to interfere with obesity-associated inflammation,” Tim Sparwasser of the Twincore Center for Experimental and Clinical Infection Research in Hannover, Germany, says in an email. Sparwasser and his colleagues had previously shown that ACC1 is required for the differentiation of Th17 cells in mice and humans.

Nakayama explains that CD4 T cells must undergo profound metabolic changes as they mature and differentiate. “The intracellular metabolites, including fatty acids, are essential for cell proliferation and cell growth,” he says in an email. When fatty acid levels in T cells increase, the cells are activated and begin to proliferate.

“It’s a nice illustration of how, really, immune response is so highly connected to the metabolic state of the cell,” says Gökhan S. Hotamisligil of Harvard University’s T.H. Chan School of Public Health who was not involved in the study. “The immune system launches its responses commensurate with the sources of nutrients and energy from the environment,” he adds in an email.

There are still missing pieces in the path from high-fat diet to increased Acaca expression to ACC1’s influence on T-cell differentiation. It also remains to be seen how this plays out in obese humans, although Nakayama and colleagues did show that inhibiting ACC1 reduced pathologic Th17 generation in human immune cell cultures, and that the T cells of obese humans contain elevated levels of ACC1 and show signs of increased differentiation into Th17 cells.

The prevalence of obesity has been increasing worldwide, and obesity is now a major public health problem in most developed countries (Gregor and Hotamisligil, 2011, Ng et al., 2014). Obesity-induced inflammation contributes to the development of various chronic diseases, such as autoimmune diseases, metabolic diseases, and cancer (Kanneganti and Dixit, 2012, Kim et al., 2014,Osborn and Olefsky, 2012, Winer et al., 2009a). A number of studies have pointed out the importance of reciprocal interactions between metabolic systems and immune cells in the pathogenesis of obesity-associated diseases (Kaminski and Randall, 2010, Kanneganti and Dixit, 2012, Kim et al., 2014, Mauer et al., 2014, Stienstra et al., 2012, Winer et al., 2011).

We herein identified a critical role that ACC1 plays in Th17 cell differentiation and the pathogenicity of Th17 cells through the control of the RORγt function under obese circumstances. High-fat-induced obesity augments Th17 cell differentiation and the expression of enzymes involved in fatty acid metabolism, including ACC1. Pharmacological inhibition or genetic deletion of ACC1 resulted in impaired Th17 cell differentiation in both mice and humans. In contrast, overexpression of Acaca induced Th17 cells in vivo, leaving the expression ofIfng and Il4 largely unchanged. ACC1 modulated the binding of RORγt to theIl17a gene and the subsequent p300 recruitment in differentiating Th17 cells. Memory CD4 T cells from peripheral blood mononuclear cells (PBMCs) of obese subjects showed increased IL-17A production and ACACA expression. Furthermore, a strong correlation was detected between the proportion of IL-17A-producing cells and the expression level of ACACA in memory CD4 T cells in obese subjects. Thus, our findings provide evidence of a mechanism wherein obesity can exacerbate IL-17-mediated pathology via the induction of ACC1.